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Cognitive Strategies

Cognitive strategies are useful tools in assisting students with learning problems. The term "cognitive strategies" in its simplest form is the use of the mind (cognition) to solve a problem or complete a task. Cognitive strategies may also be referred to as procedural facilitators (Bereiter & Scardamalia, 1987), procedural prompts (Rosenshine, 1997) orscaffolds (Palincsar & Brown, 1984). A related term is metacognition, the self-reflection or "thinking about thinking" necessary for students to learn effectively (Baker, Gersten, & Scanlon, 2002).

Cognitive strategies provide a structure for learning when a task cannot be completed through a series of steps. For example, algorithms in mathematics provide a series of steps to solve a problem. Attention to the steps results in successful completion of the problem. In contrast, reading comprehension, a complex task, is a good example of a task that does not follow a series of steps. Further explanation is provided below.

A cognitive strategy serves to support the learner as he or she develops internal procedures that enable him/her to perform tasks that are complex (Rosenshine, 1997). Reading comprehension is an area where cognitive strategies are important. A self-questioning strategy can help students understand what they read. Rosenshine states that the act of creating questions does not lead directly to comprehension. Instead, students search the text and combine information as they generate questions; then they comprehend what they have read.

The use of cognitive strategies can increase the efficiency with which the learner approaches a learning task. These academic tasks can include, but are not limited to, remembering and applying information from course content, constructing sentences and paragraphs, editing written work, paraphrasing, and classifying information to be learned.

In a classroom where cognitive strategies are used, the teacher fulfills a pivotal role, bridging the gap between student and content/skill to be learned. This role requires an understanding of the task to be completed, as well as knowledge of an approach (or approaches) to the task that he/she can communicate to the learner.

Content Enhancement

Impacting both the task and the learner using cognitive strategies is referred to as Content Enhancement. Bulgren, Deshler, and Schumaker (1997) highlight three important teacher activities in their model of content enhancement:

• Teachers evaluate the content they cover.
• Teachers determine the necessary approaches to learning for student success
• Teachers teach with routines and instructional supports that assist students as they apply appropriate techniques and strategies.

In this way, the teacher emphasizes what the students should learn, or the "product" of learning. In addition, the teacher models the how or "process" of learning.

Content Evaluation

When a teacher is comfortable with the content he/she is teaching, he/she knows which parts are the most important, the most interesting and the easiest (or hardest) to learn. The teacher evaluates the content with various questions in mind:

• How important is this information to my students?
• Is any of this information irrelevant to the point I can minimize or exclude it?
• How will my students use this information beyond my classroom (in general education classrooms, college and/or career settings, etc.)
• What parts of this information do I think my students will grasp quickly?
• What parts of this information do I think my students will need "extras" (more time, more examples, peer help, more explanation, applications, etc.)
• How should I pace the presentation?
• Which evaluations are going to help me know that my students understand this information?

The more experienced the teacher is with content, the better he/she will be able to plan students' cognitive journey through the information or skills that will be unfamiliar to them.

Determination of necessary approaches

Now the teacher's attention turns to his/her knowledge of the students. Student characteristics such as intellectual ability, interest in the subject, and general motivation to learn are considered. The teacher selects learning approaches that complement the learner characteristics while ensuring success with the content. A teacher who teaches cognitive strategies well will connect learner and task. A strategy will be chosen because it is the best strategy for BOTH the learner's characteristics and the task and/or content that needs to be mastered.

Routines and instructional supports

Once the best strategy or strategies have been selected, the teacher begins the work of teaching the strategy to the student(s). Explicit instruction is used to impart the components or steps of the strategy. Often the strategy will include actions or routines that are repeated each time the strategy is implemented. Additional instructional supports such as guided practice, independent practice, verbal practice, and written or oral tests may also be used.

A Real-Life Example

You can compare the teaching of cognitive strategies to teaching a friend to drive in your hometown. Because you are in your hometown, you know the area, or content, very well. In addition, the person you are teaching to drive is your friend, so you also know the learner well. This knowledge can make your teaching more efficient, because you have two areas of expertise (the content and the learner) at your disposal. You will use a combination of explicit instructions (turn left on Church Street) and supports (maps, the rule that "all avenues run North-South") to teach your friend how to navigate around town. You may also use verbal directions as opposed to maps, depending on your friend's preferred mode of information.

Just as important, you can avoid situations that could become barriers to learning (and your friendship). For example, if your friend tends to be anxious, you will NOT begin your instruction during rush hour!

Selected Cognitive Strategies

Because they are diverse and highly relevant to tasks, the use of cognitive strategies by teachers and students can significantly impact important learning outcomes for students. This website provides examples of cognitive strategies, with descriptions and examples. The following table presents the strategies that will be discussed. In addition, case studies will be presented to show cognitive strategies in action.

Cognitive Strategies for Special Connections

Strategy Type

Brief Description

Orienting Strategies

Student's attention is drawn to a task through teacher input, highlighted material, and/or student self-regulation.

Teacher cue to "listen carefully"Boldface type

Specific Aids for Attention

Student's attention is maintained by connecting a concrete object or other cue to the task.

A special pencil cues the student to pay special attention to punctuation when he is writing sentences.

Specific Aids for Problem-Solving or Memorization

Student's problem-solving is enhanced by connecting a concrete object or other cue to the task.

Concrete objects are used in solving math problems.

Student practices (rehearses) target information through verbalization, visual study, or other means.

Students practice vocabulary and definitions through games where they must orally repeat target information.

Elaboration

Student expands target information by relating other information to it (ex. creating a phrase, making an analogy).

Students relate the life of an ant colony to their community.

Transformation

Student simplifies target information by converting difficult or unfamiliar information into more manageable information.

Procedures for protecting oneself from being burned are learned as "Stop, Drop, and Roll".

Student transforms target information by creating meaningful visual, auditory, or kinesthetic images of the information.

Visualization of a scene described in a passage

Student transforms target information by relating a cue word, phrase, or sentence to the target information.

My Dear Aunt Sally for the order of mathematical operations (multiply, divide, add, subtract)

Organization

Student categorizes, sequences or otherwise organizes information for more efficient recall and use.

Words in lists are placed in categories.

*Imagery and Mnemonics can be considered special types of transformational strategies.

The use of cognitive strategies can increase the efficiency and confidence with which the learner approaches a learning task, as well as his/her ability to develop a product, retain essential information, or perform a skill. While teaching cognitive strategies requires a high degree of commitment from both the teacher and learner, the results are well worth the effort.

Developed by: LuAnn Jordan, Ph.D., University of North Carolina, Charlotte.

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Using technology in special education: current practices and trends

• Published: 18 June 2020
• Volume 68 , pages 1711–1738, ( 2020 )

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• Oluwabunmi Adewoyin Olakanmi   ORCID: orcid.org/0000-0001-6281-0285 1 ,
• Gokce Akcayir 1 ,
• Oluwbukola Mayowa Ishola 2 &
• Carrie Demmans Epp 1  

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Recent reports suggest an increase in the number of individuals with cognitive and developmental disabilities. To ensure equal opportunities for these learners, special education practices must be appropriately improved and scaled. Educational and assistive technologies are a possible avenue for meeting this need. To provide insight into recent technology practices in special education contexts, this study reviews recent literature (2014—2018) on the use of technology to support learners with cognitive and developmental disabilities. This review included 126 publications, which were a combination of journal articles and conference papers, found through the ACM, IEEE, ScienceDirect, and SSCI databases. The publications were analyzed to determine their general characteristics (e.g., number and age of participants and lengths of interventions), the contexts of technology use, specific learner characteristics, the subjects or skills the intervention(s) aimed to improve, the characteristics of the technologies, and the outcomes associated with their use. The results revealed that the most examined technology was games and the most studied outcome was improvements to learners’ cognitive skills. Additionally, participants in the majority of the publications were pre-college students with learning disabilities. The most studied topics belonged to the natural sciences while job skills were one of the least studied. Interventions were primarily conducted in formal educational environments and were implemented over 5–10 weeks in most cases. Based on the review, more detail in reporting and more attention to promoting life, job, and social skills are recommended.

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Home » Blog » General » Teaching Problem-Solving Skills to Special Education Students

Teaching Problem-Solving Skills to Special Education Students

Introduction

Problem-solving is a critical life skill that helps students navigate the challenges they encounter daily. By teaching problem-solving skills to special education students, educators can empower them to develop resilience and independence. In this blog post, we will explore a no-prep activity that can be used in the classroom to teach problem-solving skills, followed by discussion questions and information on related skills.

No-Prep Activity

This no-prep activity is designed to help students identify problems, determine their size, and come up with solutions. To begin, ask students to pair up and share a recent problem they faced. Next, have them discuss the following:

• What was the problem?
• Was it a big or small problem?
• What solutions did they think of to solve the problem?
• Which solution did they choose, and why?

After the pairs have discussed their problems and solutions, bring the class back together for a group discussion. Encourage students to share what they learned from their partner’s problem-solving experience. This activity helps students practice problem-solving skills in a safe and supportive environment while learning from their peers.

Discussion Questions

Use these discussion questions to further explore problem-solving skills with your students:

• Why is it important to be able to solve problems on our own?
• How can we determine if a problem is big or small?
• What are some strategies for coming up with solutions to problems?
• How can we support our friends when they are trying to solve a problem?
• Can you think of a time when you helped someone else solve a problem? How did it make you feel?

Related Skills

Teaching problem-solving skills is an essential part of social-emotional learning. Other relevant skills for students to develop include:

• Communication: Being able to express oneself clearly and listen to others is crucial for effective problem-solving.
• Collaboration: Working together with others to find solutions is an important aspect of problem-solving.
• Critical thinking: Evaluating different solutions and choosing the best one requires critical thinking skills.
• Resilience: Learning to bounce back from setbacks and continue working towards a solution is an essential skill for problem-solving.

Teaching problem-solving skills to special education students is an important part of their overall development. If you’re interested in exploring more activities and resources to support social-emotional learning, sign up for free samples of skill-building materials at Everyday Speech. You’ll find a wealth of resources designed to help students develop essential life skills and thrive in their social interactions.

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Welcome to NASET's Assessment in Special Education Series . This is an  education resource that focuses on  the process used to determine a child’s specific learning strengths and needs, and to determine whether or not a child is eligible for special education services.  Assessment in special education is a process that involves collecting information about a student for the purpose of making decisions. Assessment, also known as evaluation, can be seen as a problem-solving process.

LATEST ISSUE of NASET's ASSESSMENT IN SPECIAL EDUCATION SERIES

Required responsibilities in screening and assessment of students.

As part of the role of special educator, you may be called upon with other staff members to test students lacking intellectual or academic information in their files, or high-risk students for a suspected disability. These forms of testing require several different procedures and may range from the gathering of basic academic, behavioral, and intellectual levels to a more comprehensive assessment for participation in special education. You will also need to be aware that these procedures involve tests that may require a parent’s permission so check with the district policy. There are three procedural forms of testing that you will need to understand. In these cases, the special education teacher would be used as the educational evaluator (educational diagnostician). This role may require assessment in a variety of settings:

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PAST ISSUE OF Assessment in Special Education Series

Available issues in this series:, introduction to assessment and overview, part i -identification of high risk students, part ii -referral to the child study team, part iii -obtaining parental informed consent for assessment, part iv -understand the requirements of an evaluation for a suspected disability, part v -the multidisciplinary team and the comprehensive assessment, part vi - understand the various methods of assessment options available to the multidisciplinary team, part vii - basic statistics and scoring terminology used in assessment, part viii - understanding a students behavior during the assessment, part ix - understand the components of a professional report, part x - understand what is required for a presentation to the iep committee, part xi - what is curriculum-based measurement and what does it mean to a child, part xii - assessment and accommodations, part xiii -  the common core standards, part xiv - accommodations in assessment, part xv - special education anacronyms, part xvi - comprehensive tests of academic achievement, part xvii - special education interpreting: challenges and legal aspects, part xviii - sharing information about state assessments with families of children with disabilities, part xix - understanding screening.

An assessment in special education is the process used to determine a child’s specific learning strengths and needs, and to determine whether or not a child is eligible for special education services. Assessment in special education is a process that involves collecting information about a student for the purpose of making decisions. Assessment, also known as evaluation, can be seen as a problem-solving process (Swanson & Watson, 1989) that involves many ways of collecting information about the student. According to Gearheart and Gearheart (1990; cited in Pierangelo and Giuliani, 2006), assessment is “a process that involves the systematic collection and interpretation of a wide variety of information on which to base instructional/intervention decisions and, when appropriate, classification and placement decisions. Assessment is primarily a problem-solving process”.

Importance of Assessment

The importance of assessment should never be underestimated. In special education, you will work with many professionals from different fields. You are part of a team, often referred to as a multidisciplinary team, that tries to determine what, if any, disability is present in a student. The team’s role is crucial because it helps determine the extent and direction of a child’s personal journey through the special education experience (Pierangelo and Giuliani, 2006). Consequently, the skills you must possess in order to offer a child the most global, accurate, and practical evaluation should be fully understood. The development of these skills should include a good working knowledge of the following components of the assessment process in order to determine the presence of a suspected disability:

• Collection: The process of tracing and gathering information from the many sources of background information on a child such as school records, observation, parent intakes, and teacher reports
• Analysis: The processing and understanding of patterns in a child’s educational, social, developmental, environmental, medical, and emotional history
• Evaluation: The evaluation of a child’s academic, intellectual, psychological, emotional, perceptual, language, cognitive, and medical development in order to determine areas of strength and weakness
• Determination: The determination of the presence of a suspected disability and the knowledge of the criteria that constitute each category
• Recommendation: The recommendations concerning educational placement and program that need to be made to the school, teachers, and parents

Purpose of Assessment

Assessment in educational settings serves five primary purposes:

• screening and identification: to screen children and identify those who may be experiencing delays or learning problems
• eligibility and diagnosis: to determine whether a child has a disability and is eligible for special education services, and to diagnose the specific nature of the student's problems or disability
• IEP development and placement: to provide detailed information so that an Individualized Education Program (IEP) may be developed and appropriate decisions may be made about the child's educational placement
• instructional planning: to develop and plan instruction appropriate to the child's special needs
• evaluation: to evaluate student progress. (Pierangelo and Giuliani, 2006)

The Difference Between Testing and Assessment

There is sometimes confusion regarding the terms "assessment" and "testing." While they are related, they are not synonymous. Testing is the administration of specifically designed and often standardized educational and psychological measures of behavior and is a part of the assessment process. Testing is just one piece of the assessment process.  Assessment encompasses many different methods of evaluation, one of which is using tests. 

Role of the Education Professional in the Special Education Process

The professional involved in special education in today’s schools plays a very critical role in the overall education of students with all types of disabilities. The special educator’s position is unique in that he or she can play many different roles in the educational environment. Whatever their role, special educators encounter a variety of situations that require practical decisions and relevant suggestions. No matter which type of professional you become in the field of special education, it is always necessary to fully understand the assessment process and to be able to clearly communicate vital information to professionals, parents, and students (Pierangelo and Giuliani, 2006).

Assessment and Federal Law

The Individuals with Disabilities Education Act (IDEA), Public Law 105-476, lists 13 separate categories of disabilities under which children may be eligible for special education and related services. These are:

• autism: a developmental disability significantly affecting verbal and nonverbal communication and social interaction, generally evident before age 3
• deafness: a hearing impairment that is so severe that the child is impaired in processing linguistic information, with or without amplification
• deaf-blindness: simultaneous hearing and visual impairments
• hearing impairment: an impairment in hearing, whether permanent or fluctuating
• mental retardation: significantly subaverage general intellectual functioning existing concurrently with deficits in adaptive behavior
• multiple disabilities: the manifestation of two or more disabilities (such as mental retardation-blindness), the combination of which requires special accommodation for maximal learning
• orthopedic impairment: physical disabilities, including congenital impairments, impairments caused by disease, and impairments from other causes
• other health impairment: having limited strength, vitality, or alertness due to chronic or acute health problems
• serious emotional disturbance: a disability where a child of typical intelligence has difficulty, over time and to a marked degree, building satisfactory interpersonal relationships; responds inappropriately behaviorally or emotionally under normal circumstances; demonstrates a pervasive mood of unhappiness; or has a tendency to develop physical symptoms or fears
• specific learning disability: a disorder in one or more of the basic psychological processes involved in understanding or in using language, spoken or written, which may manifest itself in an imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations
• speech or language impairment: a communication disorder such as stuttering, impaired articulation, a language impairment, or a voice impairment
• traumatic brain injury: an acquired injury to the brain caused by an external physical force, resulting in total or partial functional disability or psychosocial impairment, or both
• visual impairment: a visual difficulty (including blindness) that, even with correction, adversely affects a child educational performance

Conclusi on

To determine if a child is eligible for classification under one of the 13 areas of exceptionality, an individualized evaluation, or assessment, of the child must be conducted. The focus of this series is to take you, the educator, step-by-step through the assessment process in special education. The following is a list of the latest and upcoming issues of this series.

Download a PDF Version of this Issue

Introduction to Assessment and Overview   - CLICK HERE

Publications

• Part I - Identification of High Risk Students
• Part 2 - Referral to the Child Study Team
• Part 3 - Obtaining Parental Informed Consent for Assessment
• Part 4 - Understand the Requirements of an Evaluation for a Suspected Disability
• Part 5 - The Multidisciplinary Team and the Comprehensive Assessment
• Part 6 - Understand the Various Methods of Assessment Options Available to the Multidisciplinary Team
• Part 7 - Basic Statistics and Scoring Terminology Used in Assessment
• Part 8 - Understanding a Students Behavior During the Assessment Process
• Part 9 - Understand the Components of a Professional Report
• Part 10 - Understand What is Required for a Presentation to the IEP Committee
• Part 11 - What is Curriculum-Based Measurement and What Does It Mean to a Child?
• Part 12 - Assessment and Accommodations
• Part 13 - The Common Core Standards
• Part 14 - Accommodations in Assessment
• Part 15 - Special Education Acronyms
• Part 16 - Comprehensive Tests of Academic Achievement
• Part 17 - Special Education Interpreting: Challenges and Legal Aspects By. Silvia Gonzalez Koch
• Part 18 - Sharing Information about State Assessments with Families of Children with Disabilities
• Part 19 - Understanding Screening
• Part 20 - Required Responsibilities in Screening and Assessment of Students

©2024 National Association of Special Education Teachers. All rights reserved

Problem-Solving Model for Improving Student Achievement

Principal Leadership Magazine, Vol. 5, Number 4, December 2004

Counseling 101 column, a problem-solving model for improving student achievement.

Problem solving is an alternative to assessments and diagnostic categories as a means to identify students who need special services.

By Andrea Canter

Andrea Canter recently retired from Minneapolis Public Schools where she served as lead psychologist and helped implement a district-wide problem solving model. She currently is a consultant to the National Association of School Psychologists (NASP) and editor of its newspaper, Communiquè . “Counseling 101” is provided by NASP ( www.nasponline.org ).

The implementation of the No Child Left Behind Act (NCLB) has prompted renewed efforts to hold schools and students accountable for meeting high academic standards. At the same time, Congress has been debating the reauthorization of the Individuals With Disabilities Education Act (IDEA), which has heightened concerns that NCLB will indeed “leave behind” many students who have disabilities or other barriers to learning. This convergence of efforts to address the needs of at-risk students while simultaneously implementing high academic standards has focused attention on a number of proposals and pilot projects that are generally referred to as problem-solving models. A more specific approach to addressing academic difficulties, response to intervention (RTI), has often been proposed as a component of problem solving.

What Is Problem Solving?

A problem-solving model is a systematic approach that reviews student strengths and weaknesses, identifies evidence-based instructional interventions, frequently collects data to monitor student progress, and evaluates the effectiveness of interventions implemented with the student. Problem solving is a model that first solves student difficulties within general education classrooms. If problem-solving interventions are not successful in general education classrooms, the cycle of selecting intervention strategies and collecting data is repeated with the help of a building-level or grade-level intervention assistance or problem-solving team. Rather than relying primarily on test scores (e.g., from an IQ or math test), the student’s response to general education interventions becomes the primary determinant of his or her need for special education evaluation and services (Marston, 2002; Reschly & Tilly, 1999).

Why Is a New Approach Needed?

Although much of the early implementation of problem-solving models has involved elementary schools, problem solving also has significant potential to improve outcomes for secondary school students. Therefore, it is important for secondary school administrators to understand the basic concepts of problem solving and consider how components of this model could mesh with the needs of their schools and students. Because Congress will likely include RTI options in its reauthorization of special education law and regulations regarding learning disabilities, it is also important for school personnel to be familiar with the pros and cons of the problem-solving model.

Student outcomes. Regardless of state or federal mandates, schools need to change the way they address academic problems. More than 25 years of special education legislation and funding have failed to demonstrate either the cost effectiveness or the validity of aligning instruction to diagnostic classifications (Fletcher et al., 2002; Reschly & Tilly, 1999; Ysseldyke & Marston, 1999). Placement in special education programs has not guaranteed significant academic gains or better life outcomes for students with disabilities. Time-consuming assessments that are intended to differentiate students with disabilities from those with low achievement have not resulted in better instruction for struggling students.

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Dilemma of learning disabilities. The learning disabilities (LD) classification has proven especially problematic. Researchers and policymakers representing diverse philosophies regarding disability are generally in agreement that the current process needs revision (Fletcher et al., 2002). Traditionally, if a student with LD is to be served in special education, an evaluation using individual intelligence tests and norm-referenced achievement tests is required to document an ability/achievement discrepancy. This model has been criticized for the following reasons:

• A reliance on intelligence tests in general and with students from ethnic and linguistic minority populations in particular
• A focus on within-child deficiencies that often ignore quality of instruction and environmental factors
• The limited applicability of norm-referenced information to actual classroom teaching
• The burgeoning identification of students as disabled
• The resulting allocation of personnel to responsibilities (classification) that are significantly removed from direct service to students (Ysseldyke & Marston, 1999).

Wait to fail. A major flaw in the current system of identifying student needs is what has been dubbed the wait to fail approach in which students are not considered eligible for support until their skills are widely discrepant from expectations. This runs counter to years of research demonstrating the importance of early intervention (President’s Commission on Excellence in Special Education, 2002). Thus, a number of students fail to receive any remedial services until they reach the intermediate grades or middle school, by which time they often exhibit motivational problems and behavioral problems as well as academic deficits.

For other students, although problems are noted when they are in the early grades, referral is delayed until they fail graduation or high school standards tests, increasing the probability that they will drop out. Their school records often indicate that teachers and parents expressed concern for these students in the early grades, which sometimes resulted in referral for assessments, but did not result in qualification for special education or other services.

Call for evidence-based programs. One of the major tenets of NCLB is the implementation of scientifically based interventions to improve student performance. The traditional models used by most schools today lack such scientifically based evidence. There are, however, many programs and instructional strategies that have demonstrated positive outcomes for diverse student populations and needs (National Reading Panel, 2000). It is clear that schools need systemic approaches to identify and resolve student achievement problems and access proven instructional strategies.

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How It Works

Although problem-solving steps can be described in several stages, the steps essentially reflect the scientific method of defining and describing a problem (e.g., Ted does not comprehend grade-level reading material); generating potential solutions (e.g., Ted might respond well to direct instruction in comprehension strategies); and implementing, monitoring, and evaluating the effectiveness of the selected intervention.

Problem-solving models have been implemented in many versions at local and state levels to reflect the unique features and needs of individual schools. However, all problem-solving models share the following components:

• Screening and assessment that is focused on student skills rather than classification
• Measuring response to instruction rather than relying on norm-referenced comparisons
• Using evidence-based strategies within general education classrooms
• Developing a collaborative partnership among general and special educators for consultation and team decision making.

Three-tiered model. One common problem-solving model is the three-tiered model. In this model, tier one includes problem-solving strategies directed by the teacher within the general education classrooms. Tier two includes problem-solving efforts at a team level in which grade-level staff members or a team of various school personnel collaborate to develop an intervention plan that is still within the general education curriculum. Tier three involves referral to a special education team for additional problem solving and, potentially, a special education assessment (Office of Special Education Programs, 2002).

Response to intervention. A growing body of research and public policy discussion has focused on problem-solving models that include evaluating a student’s RTI as an alternative to the IQ-achievement discrepancy approach to identifying learning disabilities (Gresham, 2002). RTI refers to specific procedures that align with the steps of problem solving:

• Implementing evidence-based interventions
• Frequently measuring a student’s progress to determine whether the intervention is effective
• Evaluating the quality of the instructional strategy
• Evaluating the fidelity of its implementation. (For example, did the intervention work? Was it scientifically based? Was it implemented as planned?)

Although there is considerable debate about replacing traditional eligibility procedures with RTI approaches (Vaughn & Fuchs, 2003), there is promising evidence that RTI can systematically improve the effectiveness of instruction for struggling students and provide school teams with evidence-based procedures that measures a student’s progress and his or her need for special services.

New roles for personnel. An important component of problem-solving models is the allocation (or realignment) of personnel who are knowledgeable about the applications of research to classroom practice. Whereas traditional models often limit the availability of certain personnel-for example, school psychologists-to prevention and early intervention activities (e.g., classroom consultation), problem-solving models generally enhance the roles of these service providers through a systemic process that is built upon general education consultation. Problem solving shifts the emphasis from identifying disabilities to implementing earlier interventions that have the potential to reduce referral and placement in special education.

Outcomes of Problem Solving and RTI

Anticipated benefits of problem-solving models, particularly those using RTI procedures, include emphasizing scientifically proven instructional methods, the early identification and remediation of achievement difficulties, more functional and frequent measurement of student progress, a reduction in inappropriate and disproportionate special education placements of students from diverse cultural and linguistic backgrounds, and a reallocation of instructional and behavior support personnel to better meet the needs of all students (Gresham, 2002; Ysseldyke & Marston, 1999). By using problem solving, some districts have reduced overall special education placements, increased individual and group performance on standards tests, and increased collaboration among special and general educators.

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The enhanced collaboration between general education teachers and support personnel is particularly important at the secondary level because staff members often have limited interaction with school personnel who are outside of their specialty area. Problem solving provides a vehicle to facilitate communication across disciplines to resolve student difficulties in the classroom. Secondary schools, however, face additional barriers to collaboration because each student may have five or more teachers. Special education is often even more separated from general education in secondary school settings. Secondary school teachers also have a greater tendency to see themselves as content specialists and may be less invested in addressing general learning problems, particularly when they teach five or six class periods (and 150 or more students) each day. The sheer size of the student body and the staff can create both funding and logistical difficulties for scheduling training and team meetings.

Is Problem Solving Worth the Effort?

Data from district-wide and state-level projects in rural, suburban, and urban communities around the country support the need to thoughtfully implement problem-solving models at all grade levels. There are several federally funded demonstration centers that systematically collect information about these approaches. Although national demonstration models may be a few years away, it seems likely that state and federal regulations under IDEA will include problem solving and RTI as accepted experimental options. Problem solving continues to offer much promise to secondary school administrators who are seeking to improve student performance through ongoing assessment and evidence-based instruction. PL

• Fletcher, J., Lyon, R., Barnes, M., Stuebing, K., Francis, D., Olson, R., Shaywitz, S., & Shaywitz, B. (2002). Classification of learning disabilities: An evidence-based evaluation. In R. Bradley, L. Donaldson, & D. Hallahan (Eds.), Identification of learning disabilities (pp. 185-250). Mahwah, NJ: Erlbaum.
• Gresham, F. (2002). Responsiveness to intervention: An alternative approach to the identification of learning disabilities. In R. Bradley, L. Donaldson, & D. Hallahan (Eds.), Identification of learning disabilities (pp. 467-519). Mahwah, NJ: Erlbaum.
• Marston, D. (2002). A functional and intervention-based assessment approach to establishing discrepancy for students with learning disabilities. In R. Bradley, L. Donaldson, & D. Hallahan (Eds.), Identification of learning disabilities (pp. 437-447). Mahwah, NJ: Erlbaum.
• National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific literature on reading and its implications for reading instruction-Reports of the subgroups. Washington, DC: Author.
• Office of Special Education Programs, U.S. Department of Education. (2002). Specific learning disabilities: Finding common ground (Report of the Learning Disabilities Round Table). Washington, DC: Author.
• President’s Commission on Excellence in Special Education. (2002). A new era: Revitalizing special education for children and their families. Washington, DC: U.S. Department of Education.
• Reschly, D., & Tilly, W. D. III (1999). Reform trends and system design alternatives. In D. Reschly, W. D. Tilly III, & J. Grimes (Eds.), Special education in transition: Functional assessment and noncategorical programming (pp. 19-48). Longmont, CO: Sopris West.
• Vaughn, S., & Fuchs, L. (Eds.) (2003). Special issue: Response to intervention. Learning Disabilities Research & Practice, 18(3).
• Ysseldyke, J., & Marston, D. (1999). Origins of categorical special education services in schools and a rationale for changing them. In D. Reschly, W. D. Tilly III, & J. Grimes (Eds.), Special education in transition: Functional assessment and noncategorical programming (pp. 1-18). Longmont, CO: Sopris West.

Case Study: Optimizing Success Through Problem Solving

By Marcia Staum and Lourdes Ocampo

Milwaukee Public Schools, the largest school district in Wisconsin, is educating students with Optimizing Success Through Problem Solving (OSPS), a problem-solving initiative that uses a four-step, data-based, decision-making process to enhance school reform efforts. OSPS is patterned after best practices in the prevention literature and focuses on prevention, early intervention, and focused intervention levels.  Problem-solving facilitators provide staff members with the training, modeling, support, and tools they need to effectively use data to drive their instructional decision-making. The OSPS initiative began in the fall of 2000 with seven participating schools. Initially, elementary and middle level schools began to use OSPS, with an emphasis on problem solving for individual student issues. As the initiative matured, increased focus was placed on prevention and early intervention support in the schools. Today, 78 schools participate in the OSPS initiative and are serviced by a team of 18 problem-solving facilitators. 

OSPS in Action: Juneau High School

The administration of Juneau High School, a Milwaukee public charter school with 900 students, invited OSPS to become involved at Juneau for the 2003-2004 school year. Because at the time OSPS had limited involvement with high schools, two problem-solving facilitators were assigned to Juneau for one half-day each week. The problem-solving facilitators immediately joined the Juneau’s learning team, which is a small group of staff members and administrators who make educational decisions aimed at increasing student achievement.

When the problem-solving facilitators became involved with Juneau, the learning team was working to improve student participation on the Wisconsin Knowledge and Concepts Exam (WKCE). The previous year, Juneau’s 10th-grade participation on the exam had been very low. The learning team used OSPS’s four-step problem-solving process to develop and implement a plan that resulted in a 99% student participation rate on the WKCE. After this initial success, the problem-solving model was also used at Juneau to increase parent participation in parent-teacher conferences. According to Myron Cain, Juneau’s principal, “Problem solving has helped the learning team at Juneau go from dialogue into action. In addition, problem solving has supported the school within the Collaborative Support Team process and with teambuilding, which resulted in a better school climate.”

By starting at the prevention level, Juneau found that there was increased commitment from staff members. OSPS is now in the initial stages of working with Juneau to explore alternatives to suspension.  The goal is to create a working plan that will lead to creative ways of decreasing the number of suspensions at Juneau.

Marcia Staum is a school psychologist, and Lourdes Ocampo is a school social worker for Optimizing Success Through Problem Solving.

What Is Response to Intervention?

Many researchers have recommended that a student’s response to intervention or response to instruction (RTI) should be considered as an alternative or replacement to the traditional IQ-achievement discrepancy approach to identifying learning disabilities (Gresham, 2002; President’s Commission on Excellence in Special Education, 2002). Although there is considerable debate about replacing traditional eligibility procedures with RTI approaches (Vaughn & Fuchs, 2003), there is promising evidence that RTI can systematically improve the effectiveness of instruction for struggling students and provide school teams with evidence-based procedures to measure student progress and need for special services. In fact, Congress has proposed the use of research-based RTI methods (as part of a comprehensive evaluation process to reauthorize IDEA) as an allowable alternative to the use of an IQ-achievement discrepancy procedure in identifying learning disabilities.

RTI refers to specific procedures that align with the steps of problem solving. These steps include the implementation of evidence-based instructional strategies in the general education classroom and the frequent measurement of a student’s progress to determine if the intervention is effective. In settings where RTI is also a criteria for identification of disability, a student’s progress in response to intervention is an important determinant of the need and eligibility for special education services.

It is important for administrators to recognize that RTI can be implemented in various ways depending on a school’s overall service delivery model and state and federal mandates. An RTI approach benefits from the involvement of specially trained personnel, such as school psychologists and curriculum specialists, who have expertise in instructional consultation and evaluation.

• National Center on Student Progress Monitoring, www.studentprogress.org
• National Research Center on Learning Disabilities, www.nrcld.org

This article was adapted from a handout published in Helping Children at Home and School II: Handouts for Families and Educators (NASP, 2004). “Counseling 101” articles and related HCHS II handouts can be downloaded from www.naspcenter.org/principals .

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Math IEP Goals For Special Education

Drafting IEP goals can be difficult, so here are a few math IEP goals (across various ability levels) to get you started. Please adapt and modify to meet the specific needs of your students. Keep in mind a goal should be a skill you believe is achievable by the student in 1 school year. You can always do an addendum if a student has met all criteria for the goal/objectives.

Remember, when writing objectives, break down the goal into smaller steps. You can lessen the percentage of accuracy, the number of trials (3/5 vs 4/5), or amount of prompting. Just make sure the objectives build on each other and are working towards mastery.

The reason why I always list accuracy at 100% when writing Math goals is because the answer is either right or wrong, an answer to a math problem can’t be 50% correct. So feel free to play with the ## of trials for accuracy.

Number Identification:

Goal: Student will independently identify numbers 1-20 (verbally, written, or pointing) with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: When verbally prompted by teacher to “point to the number _________”, Student will independently select the correct number with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently count in rote order numbers 1-25 with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently count by 2, 3, 5, 10 starting from 0-30 verbally or written, with 100% accuracy on 4 out of 5 trials measured quarterly.

One-to-one Correspondence:

Goal: When given up to 10 objects, Student will independently count and determine how many objects there are (verbally, written, or by pointing to a number) with 100% accuracy on 4 out of 5 trials measured quarterly/monthly.

Goal: When given up to 10 items/objects, Student will independently count and move the items to demonstrate 1:1 correspondence and identify how many there are with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given 10 addition problems, Student will independently add single digit numbers with regrouping with 100% accuracy on 4 out of 5 trials as measured quarterly.

Goal:  Student will independently add a single digit number to a double digit number with and without regrouping with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently add double digit numbers to double digit numbers with (or without) regrouping with 100% accuracy on 4 out of 5 trials measured quarterly.

Adding with Number Line:

Goal: Given 10 addition problems and using a number line, Student will independently add single digit numbers with 100% accuracy on 4 out of 5 trials measured quarterly. 

Subtraction:

Goal: Student will independently subtract a single digit number form a double digit number with and without regrouping with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given 10 subtraction problems, Student will independently subtract double digit numbers from double digit numbers with and without regrouping with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently subtract money/price amounts from one another with and without regrouping, while carrying the decimal point with 100% accuracy on 4 out of 5 trials as measured quarterly.

Goal: Using a number line, Student will independently subtract numbers (20 or less) with 100% accuracy on 4 out of 5 trials measured quarterly.

Telling Time:

Goal: Student will independently tell time to the half hour on an analog clock (verbally or written) with 100% accuracy on 4 out of 5 trials measured quarterly. 

Goal: Student will independently tell time to the hour on an analog clock (verbally or written) with 100% accuracy on 4 out of 5 trials measured quarterly.

Elapsed Time:

Goal: Given a problem with a start time and end time, Student will independently determine how much time has elapsed with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given a problem with a start time and duration of activity/event, Student will independently determine what the end time is with 100% accuracy on 4 out of 5 trials measured quarterly.

Dollar More:

Goal: Using the dollar more strategy, Student will independently identify the next dollar up when given a price amount with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently identify the next dollar amount when given a price, determine how much is needed to make the purchase, and count out the necessary amount (using fake school money) with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: When given a price, student will identify which number is the dollar amount with 100% accuracy on 4 out of 5 trials measured quarterly.      

Money Identification/Counting Money:

Goal: When given a quarter, dime, nickel, and penny, Student will identify the coin and corresponding value with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: When given a random amount of coins (all of one type), Student will independently count the coins with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: When given a mix of coins (to include quarter, dime, nickel, penny), Student will independently count the coins with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: When given a mixture of coins and dollar bills, Student will independently count the money with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: When give 2, 3, and 4 digit numbers, Student will independently round to the nearest tens, hundreds, thousands independently with 100% accuracy on 4 out of 5 trials measured quarterly.

Greater than/Less than:

Goal: Given 2 numbers, pictures, or groups of items, Student will independently determine which number is greater than/less than/equal by selecting or drawing the appropriate symbol (<,>, =) with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently count objects or pictures of objects and tally the corresponding amount (up to 15) with 100% accuracy on 4 out of 5 trials as measured quarterly.

Goal: Given a number, up to 20, Student will independently tally the corresponding number with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given data and a bar graph template, Student will independently construct a bar graph to display the data and answer 3 questions about the data with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given a line, pie, or bar graph, Student will independently answer questions about each set of data with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given data and a blank graph template, Student will independently construct the graph to display the appropriate data with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently identify the numerator and denominator in a fraction with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: When given a picture of a shape divided into parts, Student will independently color the correct sections in to represent the fraction given with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently add fractions with like denominators with 100% accuracy on 4 out of 5 trials measured quarterly.

Word Problems:

Goal: Student will independently solve one step addition and subtraction word problems with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently solve two step word problems (mixed addition and subtraction) with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently solve one and two step multiplication world problems with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently read a one or two step word problem, identify which operation is to be used, and solve it with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given a word problem, Student will independently determine which operation is to be used (+,-,x, /) with 100% accuracy on 4 out of 5 trials measured quarterly.

Even/Odd Numbers:

Goal: When given a number, student will independently identify if the number is odd or even (written or verbally), with 100% accuracy on 4 out of 5 trials measured quarterly.

Measurement:

Goal: Given varying lines and objects, Student will independently estimate the length of the object/picture, measure it using a ruler, and identify how long the object/picture is with 100% accuracy on 4 out of 5 trials measured quarterly.

Multiplication:

Goal: Student will independently solve 10 multiplication facts (2, 3, and 5 facts) with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Student will independently solve 20 multiplication facts (facts up to 9) with 100% accuracy on 4 out of 5 trials measured quarterly.

Goal: Given a division problem (where the divisor is _____), Student will independently solve it with 100% accuracy on 4 out of 5 trials measured quarterly.

Feel free to use and edit as necessary. It’s up to you how often you want to measure the goals, but remind parents that even if the goal says 5/5 times quarterly, it doesn’t mean you’re only working on it those 5 times. That is just the number of times you’ll take official data. Just make sure it’s a reasonable ## so you have time to take all the data you need. Especially if you have multiple goals/objectives to take data for!

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Why there's a special education and STEM teacher shortage and what can be done

Experts say obstacles include recruitment, funding and institutional support.

Jahsha Tabron, the 2022 Delaware teacher of the year, taught special education for more than two decades and cherished what she called the "winning moments" of growth in her students.

"[Where] you have a nonverbal student who is now able to speak in simple sentences … that's why you stay," she recently told ABC News.

But Tabron, now Brandywine High School's dean of students in Wilmington, Delaware, said her field can be a tough sell for future candidates.

"When we're talking about why we don't have a lot of people joining the profession, we're looking at the immense workload that comes along with being a special education teacher," she said.

MORE: Most of the US is dealing with a teaching shortage, but the data isn't so simple

Tabron's concern about a staffing shortage is widely shared. A nationwide survey conducted by ABC News this school year found that much of the country doesn't have enough educators -- and that in many cases, districts suffer from a lack of subject matter experts, too.

Two parts of the subject matter pool are particularly strained, according to local education officials: special education and science, technology, engineering and mathematics, or STEM.

Teachers and experts who spoke with ABC News cited the need for more money for students with disabilities and those who educate them; inadequate diversity in STEM; and underwhelming pipeline and recruiting efforts, particularly in more rural districts and for teachers of color, as major obstacles.

Special education has always been one of the most underfunded yet vital teaching positions in public schools, the experts said -- pointing to a perpetual desire for more financial support, either at the local or federal level, to help instructors doing such specialized work.

The experts said that STEM teachers are overwhelmingly white -- according to the National Center for Education Statistics (NCES), 79% are non-Hispanic or white -- even in public schools that are majority non-white, so they do not adequately reflect the students they teach, which creates an added pressure on bringing in more candidates. There's also a focus on increasing diversity in special education instruction.

By the numbers

For a recent report on teacher staffing across the country, ABC News reached out by phone and email to the overarching education departments in all 50 states as well as Washington, D.C., Puerto Rico and the U.S. Virgin Islands.

At least 40 states, the District of Columbia and the U.S. Virgin Islands -- 42 out of 53 surveyed -- reported ongoing teaching shortages.

According to an updated analysis, conducted this spring, the most acute shortages are in special education and STEM teachers.

Those findings are reinforced by research from NCES' School Pulse Panel, which started collecting information during the summer of 2021 to better understand the impact of the COVID-19 pandemic on students and educators.

The monthly NCES survey found 78% of K-12 public school principals reported that it was somewhat or very "difficult" to fill a position with a fully certified teacher for special education at the beginning of the current school year. About three-fourths of public schools also reported it was somewhat or very difficult to staff physical science (78%) and mathematics (75%) teachers.

ABC News' reporting found that 31 state education associations, agencies and departments identified special education challenges as one of their greatest needs during the 2022-2023 school year.

MORE: How schools are trying to address the national teacher shortage

What's more, over the course of the school year, almost a third of the country -- or 17 state education agencies -- also told ABC News one of their greatest challenges has been filling teaching positions in STEM.

Education Secretary Miguel Cardona said in a speech last year that collaboration is the key to raising the bar for education across America. He also spoke of teacher shortages in bilingual education, special education and STEM -- saying they impact low-income and students of color the most.

'We have a real problem'

The federal government's Office of Special Education Programs (OSEP) recognizes that many states are facing staffing challenges and is committed to trying to fix the system as a whole, according to OSEP Director Valerie Williams.

"There's data to support that we have a real problem," Williams told ABC News. "Going forward, we're going to aim to focus not just on increasing the numbers but also on diversification of the profession and finding ways for how we can get people from minority backgrounds interested in becoming teachers and get them into the pipeline."

President Joe Biden's 2024 budget proposal -- which has been criticized by conservatives for, they say, reducing economic growth by bloating the government -- is touted by supporters as addressing the gap in special education teachers, "investing $304 million to train and retain [them], specialized instructional support personnel, and paraprofessionals," according to a Department of Education spokesperson.

A recent House Republican proposal to reduce federal government spending has been criticized, too, though conservatives have pushed back on claims it would cut school funding -- calling that made up.

Tabron, in Delaware, said special education is one of the most challenging positions in a school as it not only has general instruction responsibilities but also juggles needs and disciplines that most teachers don't face.

"It's not regular teaching," she said. "You have special ed teachers who are doing the regular part of teaching, which is the planning instruction, the differentiation, the accommodations and modifications. But in addition to just that part of your job as a special education teacher, you are also responsible for creating individualized education plans (IEP) for all of your students."

She described special education teachers as akin to scientists, because they're required to know how their students' brains work.

During the onset of COVID-19, many teachers' workloads were exacerbated by school closures and remote teaching, Tabron said. Now, she said, those who have stayed are working with the same amount of pre-pandemic resources -- but their role has expanded to account for a recent increase in students who see the value of IEPs and special services.

"There was a need for special education teachers before the pandemic," Tabron said. "The need just increased afterwards."

'Our country really needs to step it up'

Connecticut science teacher Carolyn Kielma is raising awareness around the challenges in STEM staffing, too. The self-described "STEMinist" said all it takes is for people to have a drive and passion for teaching.

"Our country really needs to step it up in those careers if we're going to have productive citizens in the future," the 2023 National Teacher of the Year finalist said. "All students are gifted and all students have special needs. It's our job to figure out what those gifts are and what those needs are and marry them into the best lesson plan."

Experts, though, have told ABC News the STEM shortage is a "crisis." They said not only is the field missing teachers but there's also a dearth of aspiring applicants.

"We don't have enough people [in general] going into STEM careers, and so the downstream effect of that is we don't have enough STEM teachers," said Arthur Mitchell, executive director of the STEM Equity Alliance.

Education advocates told ABC News that college graduates with education degrees have been declining for years. The University of California at Los Angeles' Cooperative Institutional Research Program found only 4.3% of U.S. college freshmen intended to major in education in 2018, compared to 11% in 2000.

Mitchell said the absence of young teachers is hurting STEM teaching categories. However, he believes there's a "neglect" problem in higher education and that institutions have to fully commit to recruitment and outreach.

"We're looking for those who have an interest in STEM education and nurturing that," said Mitchell, whose STEM Equity Alliance serves as a pipeline for teacher education. "And, by and large, there have been no concerted efforts -- national concerted efforts -- and very few statewide or local efforts to really put more STEM teachers in classrooms."

Another problem? Rural areas are underserved

Upon graduation many teachers are hesitant to explore rural parts of the U.S., according to education officials around the country.

Colorado's state education talent unit said that geographical barriers are straining their most rural, and already struggling, districts.

"Math and special education shortages can affect rural areas more acutely," Colorado's Associate Commissioner of Educator Talent Colleen O'Neil told ABC News in a statement. "[Rural parts] sometimes have no candidates at all that apply for a position," she added.

Along the Pacific coast, Siskiyou County's Allan Carver said his district also faces these roadblocks because it is in the "sticks" of Northern California.

"There's not a lot of people who want to live way out here where there's no Walmart and those sorts of things," said Carver, the Siskiyou Office of Education superintendent.

Working with a limited pool is something Southeast Arkansas Education Service Cooperative Director Karen Eoff understands as well as Carver.

According to the state's department of education, Arkansas faces its worst staffing shortages in secondary math and secondary science. But from elementary education on up, Eoff said all subjects in the rural parts of her state are impacted.

"Keeping and attracting young people to this area is a problem -- we have the largest teacher shortage in Arkansas," Eoff, who oversees 15 school districts, told ABC News.

More -- and more diverse -- pipeline programs needed

Experts interviewed for this story suggested pipeline programs could be the key to preparing teachers to enter the field in the years to come.

Reach University, a job-embedded teacher apprenticeship program, has been one solution for places like rural Arkansas and California, which are far from their state's largest institutions for training future educators.

In both Southeast Arkansas and in Siskiyou County in California, Reach University said it did an extensive analysis to define current vacancies by grade level and subject, across all open positions. In Siskiyou, they found slightly elevated vacancies in elementary education and math. Special education is "always" a constant need in his district, according to Carver.

"We've got to figure out how to take people who are already happy being in schools and help them become our teachers," Carver said. "The Reach model, with the apprenticeship, was just a home run for us."

Eoff's office has used Reach since the beginning of the current school year to stem its shortages. Now, she said, it has 20 paraprofessional staffers in an apprenticeship.

"Reach has been one of our best tools because of the support, affordability, the 'come alongside and we will help you' approach," Eoff said.

In response to former President Barack Obama's 2011 call to increase the STEM teacher pool by 100,000 in a decade, education nonprofit Beyond100K used "radical collaboration" with more than 300 organizations to exceed that benchmark. The group said it helped prepare 108,000 STEM teachers -- and counting -- with a new target of 150,000 by 2032.

Part of Beyond100K's focus, according to its 2022 trends report, is to add more teachers of color to reflect the students in their classrooms, especially Black, Latino and Native American teachers.

​"The work that we are doing now is very focused on racial equity and on creating belonging for teachers and for students," Amber Hamilton, Beyond100K's chief external officer, said.

Eoff, in Arkansas, stressed how instilling that sense of belonging into students of all ages and backgrounds will hopefully guide more candidates to the field.

"I think that the earlier we encourage kids to believe they can, in STEM programs, the better," she said.

Meanwhile, as responsibilities from the pandemic grow, STEM and special education professionals agree the shortages will persist if more isn't done to help them win.

"I think that would be awesome to ask teachers what they really need," Tabron said. "Imagine someone asking you: What would make you happier here? What can I do to support you? Just you listening to that -- I think would change my performance."

ABC News' Gabe Ferris contributed to this report.

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Ieee spectrum, follow ieee spectrum, support ieee spectrum, enjoy more free content and benefits by creating an account, saving articles to read later requires an ieee spectrum account, the institute content is only available for members, downloading full pdf issues is exclusive for ieee members, downloading this e-book is exclusive for ieee members, access to spectrum 's digital edition is exclusive for ieee members, following topics is a feature exclusive for ieee members, adding your response to an article requires an ieee spectrum account, create an account to access more content and features on ieee spectrum , including the ability to save articles to read later, download spectrum collections, and participate in conversations with readers and editors. for more exclusive content and features, consider joining ieee ., join the world’s largest professional organization devoted to engineering and applied sciences and get access to all of spectrum’s articles, archives, pdf downloads, and other benefits. learn more →, join the world’s largest professional organization devoted to engineering and applied sciences and get access to this e-book plus all of ieee spectrum’s articles, archives, pdf downloads, and other benefits. learn more →, access thousands of articles — completely free, create an account and get exclusive content and features: save articles, download collections, and talk to tech insiders — all free for full access and benefits, join ieee as a paying member., ai copilots are changing how coding is taught, professors are shifting away from syntax and emphasizing higher-level skills.

Generative AI is transforming the software development industry. AI-powered coding tools are assisting programmers in their workflows, while jobs in AI continue to increase. But the shift is also evident in academia—one of the major avenues through which the next generation of software engineers learn how to code.

Computer science students are embracing the technology, using generative AI to help them understand complex concepts, summarize complicated research papers, brainstorm ways to solve a problem, come up with new research directions, and, of course, learn how to code.

“Students are early adopters and have been actively testing these tools,” says Johnny Chang , a teaching assistant at Stanford University pursuing a master’s degree in computer science. He also founded the AI x Education conference in 2023, a virtual gathering of students and educators to discuss the impact of AI on education.

So as not to be left behind, educators are also experimenting with generative AI. But they’re grappling with techniques to adopt the technology while still ensuring students learn the foundations of computer science.

“It’s a difficult balancing act,” says Ooi Wei Tsang , an associate professor in the School of Computing at the National University of Singapore . “Given that large language models are evolving rapidly, we are still learning how to do this.”

Less Emphasis on Syntax, More on Problem Solving

The fundamentals and skills themselves are evolving. Most introductory computer science courses focus on code syntax and getting programs to run, and while knowing how to read and write code is still essential, testing and debugging—which aren’t commonly part of the syllabus—now need to be taught more explicitly.

“We’re seeing a little upping of that skill, where students are getting code snippets from generative AI that they need to test for correctness,” says Jeanna Matthews , a professor of computer science at Clarkson University in Potsdam, N.Y.

Another vital expertise is problem decomposition. “This is a skill to know early on because you need to break a large problem into smaller pieces that an LLM can solve,” says Leo Porter , an associate teaching professor of computer science at the University of California, San Diego . “It’s hard to find where in the curriculum that’s taught—maybe in an algorithms or software engineering class, but those are advanced classes. Now, it becomes a priority in introductory classes.”

“Given that large language models are evolving rapidly, we are still learning how to do this.” —Ooi Wei Tsang, National University of Singapore

As a result, educators are modifying their teaching strategies. “I used to have this singular focus on students writing code that they submit, and then I run test cases on the code to determine what their grade is,” says Daniel Zingaro , an associate professor of computer science at the University of Toronto Mississauga . “This is such a narrow view of what it means to be a software engineer, and I just felt that with generative AI, I’ve managed to overcome that restrictive view.”

Zingaro, who coauthored a book on AI-assisted Python programming with Porter, now has his students work in groups and submit a video explaining how their code works. Through these walk-throughs, he gets a sense of how students use AI to generate code, what they struggle with, and how they approach design, testing, and teamwork.

“It’s an opportunity for me to assess their learning process of the whole software development [life cycle]—not just code,” Zingaro says. “And I feel like my courses have opened up more and they’re much broader than they used to be. I can make students work on larger and more advanced projects.”

Ooi echoes that sentiment, noting that generative AI tools “will free up time for us to teach higher-level thinking—for example, how to design software, what is the right problem to solve, and what are the solutions. Students can spend more time on optimization, ethical issues, and the user-friendliness of a system rather than focusing on the syntax of the code.”

Avoiding AI’s Coding Pitfalls

But educators are cautious given an LLM’s tendency to hallucinate . “We need to be teaching students to be skeptical of the results and take ownership of verifying and validating them,” says Matthews.

Matthews adds that generative AI “can short-circuit the learning process of students relying on it too much.” Chang agrees that this overreliance can be a pitfall and advises his fellow students to explore possible solutions to problems by themselves so they don’t lose out on that critical thinking or effective learning process. “We should be making AI a copilot—not the autopilot—for learning,” he says.

“We should be making AI a copilot—not the autopilot—for learning.” —Johnny Chang, Stanford University

Other drawbacks include copyright and bias. “I teach my students about the ethical constraints—that this is a model built off other people’s code and we’d recognize the ownership of that,” Porter says. “We also have to recognize that models are going to represent the bias that’s already in society.”

Adapting to the rise of generative AI involves students and educators working together and learning from each other. For her colleagues, Matthews’s advice is to “try to foster an environment where you encourage students to tell you when and how they’re using these tools. Ultimately, we are preparing our students for the real world, and the real world is shifting, so sticking with what you’ve always done may not be the recipe that best serves students in this transition.”

Porter is optimistic that the changes they’re applying now will serve students well in the future. “There’s this long history of a gap between what we teach in academia and what’s actually needed as skills when students arrive in the industry,” he says. “There’s hope on my part that we might help close the gap if we embrace LLMs.”

• How Coders Can Survive—and Thrive—in a ChatGPT World ›
• AI Coding Is Going From Copilot to Autopilot ›
• OpenAI Codex ›

Rina Diane Caballar is a writer covering tech and its intersections with science, society, and the environment. An IEEE Spectrum Contributing Editor, she's a former software engineer based in Wellington, New Zealand.

Yes! Great summary of how things are evolving with AI. I’m a retired coder (BS comp sci) and understand the fundamentals of developing systems. Learning the lastest systems is now the greatest challenge. I was intrigued by Ansible to help me manage my homelab cluster, but who wants to learn one more scripting language? Turns out ChatGPT4 knows the syntax, semantics, and work flow of Ansible and all I do is tell is to “install log2ram on all my proxmox servers” and I get a playbook that does just that. The same with Docker Compose scripts. Wow.

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Outstanding Maths Lesson for Interview/Lesson Observation Problem Solving - Years 5 and 6

Subject: Mathematics

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An exceptional maths problem solving lesson, complete with written lesson plan and interactive slides. Crafted to engage and challenge high-ability Year 5/6 students, this lesson offers a rich tapestry of activities and tasks designed to ignite mathematical thinking.

Perfect for a lesson observation or job interview, these comprehensive materials will impress all observers and demonstrate your expertise in delivering high-quality maths education.

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Revolutionizing Career Readiness: The Role of Tech in Work-Based Learning Programs

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This is a recap of a session from the 2024 ASU+GSV Summit. Watch the full session below.

In today's rapidly evolving job market, there's a crisis brewing: students are increasingly ill-prepared for the workforce. Entry-level positions are vanishing with the rise of AI and universities are struggling to prepare students for on-the-job success, leaving many feeling stranded and unqualified. But amidst this challenge lies an opportunity to bridge the gap between education and employment through innovative solutions like work-based learning programs.

Lack of Work-Based Learning Opportunities

According to a recent report from ECMC and VICE Media, a staggering 79% of high school students recognize the importance of on-the-job learning experiences during their postsecondary education. However, only half of them have access to career exploration programs. This glaring disparity underscores the urgent need for a shift in educational paradigms.

The Solution: Third-Party Organizations Connecting Employers and Learners

Enter tech-driven enterprises like Juvo Ventures , a pioneering early-stage venture capital firm founded in 2019. They're at the forefront of redefining career readiness by championing initiatives that connect students with real-world work experiences. Leaders like Dr. Courtney Hills McBeth , provost and chief academic officer at Western Governors University ( WGU ), and Katie Fang , founder and CEO of SchooLinks, which focuses on college and career readiness, are also leading the charge in revolutionizing traditional education models. 

Dana Stephenson , co-founder and CEO of Riipen , a work-based learning platform for educators, learners and employers emphasized the importance of providing students with practical experience throughout their educational journey at the 2024 ASU+GSV Summit. He highlighted the shift away from relying solely on post-graduation employment as a launching pad for careers, advocating instead for early and continuous exposure to real-world scenarios.

Dr. Ryan Craig , managing director of Achieve Partners , stressed the need for scalable solutions that seamlessly integrate employers into the education ecosystem. “You have to make it so easy that it’s turnkey for employers,” he said, underscoring the pivotal role of intermediaries in facilitating work-based learning experiences and streamlining pathways to employment. 

A Plea for Universities to Reprioritize

Dr. Hills McBeth said a key issue is focus, funding and scale, stating, “Most traditional higher ed has invested in athletics and alumni engagement and advancement offices rather than investing in employer engagement.”  

WGU is changing that as a university that has prioritized student experience and career outcomes from the start. A nonprofit founded in 1997 by 19 U.S. governors, the online university supports students through job-aligned degree programs crafted with input from employers and built for career success. Organizations that hire WGU grads are reaping the rewards with a healthy 98% of employers saying WGU graduates meet or exceed their expectations. 

Making it Easier for Employers to Connect with Learners

Solving the career-readiness challenge is not just about connecting students with opportunities; it's also about empowering employers, especially small and medium-sized enterprises, to actively participate in shaping the future workforce. Stephenson pointed out that many companies are eager to collaborate and engage with educational institutions to identify and nurture talent, citing the success of Juvo Ventures.

One key takeaway from this discussion is the importance of making work-based learning programs accessible and adaptable. Whether it's through shorter-duration, lower-intensity experiences or more immersive apprenticeships, flexibility is paramount to accommodating the diverse needs of students and employers alike. 

More Focused State Standards

There's a growing consensus on the need for clearer, more prescriptive college and career readiness standards. Ryan Craig highlighted the current generic nature of state-level standards and calls for a more tailored approach to ensure students are equipped with the skills demanded by today's job market. 

A Collaborative Effort

The revolution in career readiness isn't just about preparing students for specific jobs; it's about cultivating a mindset of adaptability, resilience, and continuous learning. By harnessing the power of technology and collaboration between states, organizations, universities, and learners, we can transform education from a passive experience into a dynamic journey that empowers individuals to thrive in an ever-changing world. 

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Suburbanization Problems in the USSR : the Case of Moscow

• Référence bibliographique

Gornostayeva Galina A. Suburbanization Problems in the USSR : the Case of Moscow . In: Espace, populations, sociétés , 1991-2. Les franges périurbaines Peri-urban fringes. pp. 349-357.

DOI : https://doi.org/10.3406/espos.1991.1474

www.persee.fr/doc/espos_0755-7809_1991_num_9_2_1474

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Résumé (fre)

La suburbanisation n'existe pas en URSS au sens des phénomènes décrits dans les villes occidentales. Cependant on observe certains transferts limités d'activités industrielles exigeantes en espace ou polluantes, voire même de centres de recherches, vers les zones suburbaines ou des villes-satellites. Mais ces déconcentrations répondent à une logique de planification administrative. En outre, les Moscovites hésitent à aller habiter dans ces centres d'emploi, de crainte de perdre les privilèges liés à l'autorisation d'habiter Moscou (la propiska) et du fait des communications insuffisantes avec la capitale. Le taux de croissance de la population moscovite reste supérieur à celui du reste de l'oblast. Par contre le développement de datchas de seconde résidence est très important dans l'oblast de Moscou, en particulier aux alentours des stations de chemin de fer. L'abolition du système de propiska pourrait transformer les datchas les plus proches de Moscou en résidences principales.

Résumé (eng)

The suburbanisation does not exist as such in the USSR with the meaning one has of the phenomena in Western cities. Though one may notice some limited transfers of industrial activities demanding a lot of space or polluting ones, even research centres, towards the suburban areas or satellite-towns. But these déconcentrations correspond to an administrative planification logics. Moreover the Muscovites hesitate before going and living in these employment centres, because they are afraid of loosing the privileges linked with the authorisation to live in Moscow (the propiska) and because of insufficient communications with the capital. The growth rate of the Muscovite population remains higher than this of the remainder of the oblast. To the contrary developing of datchas for second residences is very high in the Moscow oblast, especially in the vicinity of a railway station. The abolishment of the «propiska» system might transform the datchas nearer to Moscow into main residences.

• Economic structure [link]
• Suburbanization of activities [link]
• Suburbanization of population [link]
• Conclusions [link]
• Literature [link]

Liste des illustrations

• Table 1. Employment structure, % [link]
• Table 2. Annual rate of population increase, % [link]
• Fig. 1. Spatial distribution of country-cottages and gardening associations in the Moscow region [link]

Texte intégral

Galina A. GORNOSTAYEVA

Moscow University

Suburbanization Problems

in the USSR :

the Case of Moscow

Suburbanization processes typical to cities in Western Europe, the USA and other countries are not observed in the USSR or they are distorted to such an extent that they may not be compared with existing standards. This states the question how Soviet cities-succeeded in escaping this stage of urban development. In order to answer this question, we should first summarize the main aspects of Western suburbanization.

Firstly, it is well known that the urbanization processes are linked to structural changes in the economy. Thus the transition from the stage of concentration to this of suburbanization is associated with industrialization, and the transition to the third stage - déconcentration - is related with the rapid growth of employment in the non-industrial sphere. Secondly, a suburbanization of economic activities can be distinguished. It applies in the first place to the building and iron- working industry, transports, engineering and chemical works. These are polluting and requiring extensive areas. This suburbanization of industry is caused by the following factors: rising demand for land from firms ; worsening of transport

tions in the inner cities ; demand for lower land costs and taxation levels in suburbs ; rapid growth of road transports; state policies regulating the growth of large cities ; migration of the labour force to the suburban zones. Scientific and educational activities are also transferred from the centre to the suburbs.

The third important aspect of suburbanization applies to the population. In the suburbs two opposite flows of population meet ; one is centripetal, coming from non- metropolitan regions, the other is centrifugal, coming from the central city. The reasons for the migration to the suburbs are as follows : declining living standards in large cities (overcrowding, slow housing renewal, environmental problems, etc.); growth of motorization of the population, development of communications (telephone, telex, fax, computer) ; intensifying decentralization of working places ; lower land prices in the suburbs ; state support for the intensification of real estate development in the suburbs. The above-mentioned factors and reasons for suburbanization are altered in the Soviet cities. Let us explore them, by taking for example the largest one - Moscow.

Economic structure

The employment structure in the USSR reveals sharp differences from those in developed urbanized countries. The USSR is characterized by a high share of employment in agriculture, industry, construction and a low share in the non-industrial sphere (tab. 1).

A correlation analysis of the percentage of urban population and employment in the different spheres of economic activity reveals that the share of urban population in the USSR is higher than in countries with the same percentage of persons employed in agriculture.

TABLE 1. EMPLOYMENT STRUCTURE,

Source: personal calculations.

The urbanization processes in the Moscow Capital Region (MCR) are more intensive than in other regions of the USSR. Structural changes are more obvious here : the share of employment in the non-industrial sphere increases more substantially and the percentage of persons employed in industry and agriculture is lower than in the whole country. However the MCR cannot therefore be compared with a metropolitan region in a Western country. Although Moscow is the most advanced agglomeration in the USSR, it lags is far behind the major world cities in terms of development and it is at the very start of the post- industrial stage of its structural and urban transformation.

The structural «anomaly» of the USSR as a whole and of the MCR in particular is explained by the enforced process of industrialization (starting from the thirties) at the expense of the peasantry (thus, there is not only a booming industrial employment in cities, but also worsening living and working conditions in villages and forced collectivization having triggered off the massive rural emigration). As a result, the share of urban population in the USSR is higher than expected, based on changes in the economic structure. While urbanization in the developed countries was due, among

other causes, to an increasing labour efficiency in agriculture, this remained quite low in the USSR. Therefore the employment share in agriculture is overstated in comparison with countries with a similar percentage of urban population, and even this considerable part of the labour force is unable to feed the whole population of the country.

The share of agricultural employment in the mcr increased from 7,4 % to 7,6 °7o between 1980 and 1985 (as a result of Moscow attractiveness and the better living standards in its surrounding villages), whereas it continued to decline in other parts of the Central region. The population growth in villages adjacent to Moscow is especially intensive, though labour efficiency in localities near Moscow is higher than in the other oblasts. In spite of this, Moscow oblast provides only 61 % of milk, 34 °/o of potatoes, 45 % of vegetables and 23 % of meat needed by the population in Moscow city and oblast (Argumen- ty i facty, 1988, N50, p. 3). The structural anomaly is not only related to processes in agricultural sphere but also in industrial sector. As a result of the low economic mobility of socialist firms and of the absence of market relations, the industrial development was extensive,

without significant increases of the labour

productivity.

Thus the employment transfer from the

agricultural to the industrial sector, their

extensive development and their low labour

productivity are intrinsically related with the political definition of productiorfrela- tions and course of structural economic transformation.

Suburbanization of activities

Moscow and Moscow oblast show divergent economic structures and changes (tab. 1). In Moscow the employment share in the non-industrial sphere in Moscow is growing more rapidly, whereas the share of industrial employment is decreasing. In Moscow oblast the part of transport and communication infrastructure, retail trade, administration, housing (presently less developed than in Moscow) is increasing. Some stages in the transformation of activities in the mcr's settlements may be pointed out here. The stage of industrialization and reconstruction after World War II is characterized by the swift industrial development and the active restructuration of the Moscow and Moscow oblast economy. New industries have been built (motor-car and aircraft assembly, machine-tool industry, organic synthesis, etc.), around Moscow research and production potential. Nevertheless, this restructuration is extensive, since traditional industries don't curtail production. It favours the heavy concentration of modern functions in Moscow. There is no transfer of firms outside Moscow. Suburbanization of industrial activities did not occur because of the state owning the means of production and of thé socialist form of production relations. When research and technological progress are slowing down, these firms become inefficient and spatially immobile. The period 1956-1970 is marked by an intensive development of the region scientific sphere and by the rise of « satellite » urban policy. The new centres were specialized in modern branches of machinery and research-engineering activities and were undoubtedly very attractive for the population. Therefore towns like Dubna were growing rapidly. While the aim was to redirect part of Moscow population

growth, they display a quite specific relation with the capital. For instance, Muscovites working in Pushchino cannot reach their job every day because they lack transport facilities. Nevertheless, they don't wish to move and register their passports in the city in which they actually work, since they would have to give up their Moscow registration and then lose all Moscow privileges (see further). These new centres are isolated from information sources in Moscow. Poor telephone communications, lack of computers and telex systems hamper contacts and teamwork with colleagues in the city. It seems that material resources for experimental work in research centres are not sufficient to compensate for lack of information and communications. At the same time, poor transport links with Moscow and the other towns of Moscow oblast isolate the scientists from the higher standard of culture in the centre and from a well developed social infrastructure. An original home-work relation can be observed in Dubna: the Muscovites get the second registration of passports and live there in hostel apartments during 4 or 5 working days, during the weekends they go back to Moscow, where their families are living. The change of functions in Moscow oblast towns is still going on. Inside the towns of the first circle adjacent to Moscow, the share of employment in the non-industrial sectors and transport is growing. Inside the towns of the second circle (suburban zone) these changes lead to an increasing potential of non-industrial, industrial and construction functions. Finally, in the outlying parts of the region the further grovth of construction and industrial functions is observed and the organization potential is intensifying in some towns. The mcr towns display a crawling concen-

tration of the regional most important functions and their extension outside the boundaries of Moscow to the towns of the suburban zone. But the déconcentration of functions in the mcr is not only of natural- economic character. It also results from the state urban policy. Déconcentration is not related to the search for more advantageous sites for firms and institutions as regards to economic or social relations (the availability of cheaper labour force or more comfortable living conditions, etc.), nor is it sustained by the expansion of transport and communication facilities. Thus, this déconcentration is independent from curtailment of any function in central Moscow, whose potential is still growing, and it is also completely inadequate regarding the continuing concentration of population (see below). All this, together with the slow economic and territorial mobility of firms, is an obstacle to the economic restructuration of the region, and to the reorientation of Moscow and its suburbs to non-industrial activities and to progressive scientific and informational work. The mass labour-consuming functions still remain in Moscow and its suburbs, but they are inevitably cut off from modern types of activities.

The idea of alleviating Moscow's development appeared from the very beginning of its rapid growth, since the excessive concentration of population and employment led (as in the other major world cities) to environmental discomfort, worsening of transport, strip-holding of land and other congestion signs. In market economies, the firms react to alterations of economic or social conditions by their mobility: some

of them close, other relocate in more convenient places. In the USSR, the problem of firm transfer (unhealthy or unprofitable firms) becomes unsolvable because of the special type of production relations. Economic and territorial passivity of firms is apparent in the difficulties of erecting industrial buildings and dismantling machinery and equipment, in the low turnover of the means of production. The same problem exist regarding the labour force. Firms transferred to the suburban towns of Moscow oblast are encountering great difficulties in recruiting staff in sufficient numbers and of required skill. The local labour force is rather weak, while the Moscow workers wouldn't leave the capital to follow their firm, because they are afraid of being deprived of passport registration in Moscow. From the social point of view, giving up a Moscow registration is more significant to people than losing their job. The processes going on in the mcr are therefore not quite comparable with those in the Western world. The market economy is more «lively» and replacement of functions has the character of territorial waves. Some functions disappear while new ones emerge. In the mcr, the waves are replaced by stratification. New functions do not replace the old ones, but joining them. At the same time, this process of relative déconcentration of functions overpass the process of stable concentration of population. In the mcr, the modern branches are gravitated closely to Moscow, where skilled workers are retained by their registration advantages. Suburban towns have to be satisfied with commuters or specialists from the outlying regions of the USSR.

Suburbanization of population

The urbanization structure of the region is characterized by the predominance of its main centre - Moscow. The share of the capital in the total Moscow oblast population was as follows: in 1929 - 44,3 Vo, in 1939 - 51,6 %, in 1959 - 54,9 %, in 1979 -54,5 Vo, in 1985 - 57,3 % (Moscow Capital Region, p. 137.). Within the agglomeration, the share of Moscow is still higher, in 1959 it was 75,5 % and in 1985

- 67,3 % (ibid., p. 141), whereas in the highly developed capital regions of the world the agglomeration counts one half or less of the total population and of the economic potential, the second half being concentrated in the suburbs (Gritsay, p. 71). Moreover, the growth rate of Moscow population is higher than that of Moscow oblast (tab . 2).

TABLE 2. ANNUAL RATE OF POPULATION INCREASE,

Migrations are of great importance to the mcr. The internal migration of rural population to the cities is rather substantial, and the immigration flow from the rest of the USSR is not compensated by the decrease of rural population in the mcr. The nearer a town to Moscow, the larger the migration share in its total population increase.

The dynamics of population in the mcr has a specific character. In agglomerations of the developed countries the principle of the «broken glass» summarizes the suburbanization process. When, for some reasons, the centre loses its attractiveness the urban population moves to suburbs in search of higher living standard. In Moscow agglomeration the principle of the «overfilled glass» is operating. People wanting to live in Moscow cannot enter the city and are forced to settle near it. In Moscow immigration undoubtedly prevails over emigration, confirming the extreme territorial differentiation in conditions, level and way of life. As a rule, commuting is oriented from suburbs to Moscow (600 thousand persons come to Moscow and only 200 thousand leave it), but it accounts only for 12-15 % cf the total employment in Moscow's economy. Moreover, these commuters are not Muscovites but potential new inhabitants of the capital (striving for passport registration and domicile in Moscow).

Moscow became the most attractive place for living and an intensive flow of ruined rural residents as well as residents from other regions of the country were rushing -to Moscow. These processes were generated not only by the inception of the country structural economic transformation,

but also by the policy of special privileges for Moscow. These privileges came into being after the establishment of a centralized distribution system. Such a system involves the assignment of a priority level of foodstuffs and manufactured goods to each territory. Moscow was awarded the highest priority level. From the very beginning, better living standards and higher income for certain population categories were established there. In the thirties the artificial differentiation in living standards was confirmed by imposing restrictions to passport registration in the capital, and also by the division of administrative bodies into Moscow and Moscow oblast authorities. In the period 1925-30 dozens of new large firms were located in Moscow, but housing was insufficient at that time. Therefore, a great number of migrants from every corner of the country came to get a job in Moscow and settled in cottages in the nearby countryside. Soon, these settlements in the nearby countryside. Soon, these settlements turned into urban ones. For example, towns like Mytishchi and Luberstsy developed rapidly, and even Muscovites moved there when the railways were electrified. This was clearly the outset of a suburbanization process, but it stopped as soon as the restrictions on passport registration in Moscow were imposed and the social barrier between Moscow and Moscow oblast was established. In the period 1930-40, new industrial developments were banned from Moscow and firms drawn towards the city were located on the outskirts thus causing a rapid growth of the old and new towns. Although the development of cottages as second residence near Moscow started even before the revolution, since the en-

vironmental degradation of Moscow was practically completed at that time, they became the main resorts of those years. They had flourished in the districts with privileged natural conditions and convenient transport services (not further than 2 km from a railway station). In the period 1930-40, this sprawl of leisure housing carried on - cottage settlements expanded into an entire belt of scattered one- storeyed buildings. But at the same time, urban multi-storeyed housing also increased and after World War II these multi- storeyed buildings were found in the cottage settlements of the leisure zone. In the period 1950-60 a network of gardening associations was established. In those

years the most convenient land near Moscow had already been built on. The gardening plots allotted to the Muscovites were located in the remote parts of the mcr, outside the suburban zone, and very frequently they were on improper territories. Because of their remoteness, the difficulties in cultivation and building, the lack of infrastructure, these plots cannot become effective leisure resorts. More frequently Muscovites use them for fruit and vegetable growing.

The desire of the Muscovites for having a second residence in the suburbs can be interpreted as an unfulfilled suburbanization tendency. This desire has the same, mainly environmental, causes as suburbaniza-

tion in Western countries. The cottages within the reach of Moscow's traffic and having access to appropriate infrastructure and amenities, might become the principal residence of Muscovites if passport registration is abolished. The restrictions of passport registration in Moscow fixed in the thirties were devised as an administrative solution against the effects of Moscow's unique attractiveness and not as a means of eliminating the attractiveness itself. For this reason, Moscow became even more attractive, like a forbidden fruit. The consequences were both the concentration of the upper strata of society in the city and the extensive development of industry, resulting in a growing shortage of unskilled labour.

The shortage of regular workers in Moscow is sometimes explained by the increasing number of working places. An adequate planning of the «limiters» (1) system is then put forward as the solution for controlling the growth of Moscow is found in (Glushkova, 1988, p. 43). To be frank, about twenty industrial units and more than one hundred scientific institutions were already created in the seventies alone, in spite of the industrial building ban in Moscow, only a few firms moved outside the city in return. New industrial units easily find staff, since they offer new machinery, relatively good working conditions and higher wages. New scientific and administrative institutions are in a similar position. But the situation is totally different in the old industrial units, with rundown equipment and a high level of manual tasks. Those units suffer from a staff shortage. Moreover, as in any other city, there is a social mobility in Moscow, in most cases improving - from manual up to mental, from unskilled up to highly skilled work. Furthermore, the prestige of a higher education (university) is overestimated in Moscow, whereas the prestige of the manual professions has declined as a result of the stagnation of reinvestments in industry, the high share of manual labour (40 %), and also favouritism and

crowding in the administrative staffs. The attractiveness of an upper class position is therefore overestimated, and social mobility activated. Since Moscow cannot admit free «immigrants» the lower strata of the social structure are vacant and there appears a shortage of unskilled labour force. The lower strata of the social structure were filled in with « limiters ». Available employment in Moscow was not the cause of an organized immigration flow, but represented the only possible way to register the passport there. Roughly half of these people drawn into Moscow's economy left their jobs. «Limiters» get the right to register their passports in Moscow and take up their residence in new houses when their contract expires. They usually quit their job as soon as possible in search of better working conditions (Glushkova, 1988, p. 42). The nature of unskilled work in Moscow and the associated working conditions are so unattractive that it is nearly impossible to find Muscovites willing to perform them.

The institution of passport registration raised many problems. Thus the « limiters » are recruited in social groups not needing most of the advantages of a large city, their psychology and value system differ sharply from native Muscovites. The direct environment of the hostels where «limiters » live, has a pronounced criminal character. Fictitious marriage in order to register the passport in Moscow has become a widespread practice.

Moscow's environmental problems can hardly be solved as long as passport registration exists. The population is literally locked up within the city boundaries. Notwithstanding the environmental stresses, the Moscow privileges prevent the Muscovites from leaving the city. The urban districts not saturated with harmful industrial units are the most prestigious. The social and economic causes of Moscow's extensive growth reveal that its problems are a reflection of the ones facing the USSR. The concentration of economic, social and management functions in Mos-

cow in Soviet times materializes the strong centralism of the particraty and weighs down on the city's development. Low labour efficiency in agriculture and sheer desolation of villages on the one hand, rapid but extensive industrialisation together with forced increasing social attraction of Moscow, confirmed by the restrictions on passport registration, on the other hand, were the key factors of the mcr's polarization during decades. Together with objective factors found in other large cities of the world, subjective factors related to the Soviet political and economic system influence Moscow's growth.

The objective factors are as follows: the diversity of employment in the capital, the emergence of new types of occupations, the concentration of high-skilled and creative labour, the higher living standards, the large educational and cultural opportunities.

The subjective factors are the higher supply level of foodstuff and manufactured goods different than in other regions (the existence of meat-rationing system in many regions of the country and its absence in Moscow establishes a significant threshold not only in terms of supply but also in the outlook of the population); the lack of communications and individual motorized transport (in the rsfsr one counts 47 cars per 1000 urban inhabitants against 560 in the USA) (Argumenty i facty, 1988, N47, p. 2); the craving for joining the upper social classes and for accessing neighbourhoods with a high quality of life; unjustified promotion of upward social mobility releasing «the ground floors» of Moscow's economy; continued growth of employment due to the extensive economic development and the low economic and territorial mobility of firms. Today, the hierarchy of priorities for selecting a residence within the mcr and the whole country is as follows. Food supply comes first. The supply of manufactured

goods, the opportunities to obtain better and larger living quarters and to accede to a prestigious employment with a wage increase, social promotion, well developed consumer services come next. And only at the end of the scale appears the opportunity to fulfil cultural needs and education. Thus, there is a process of «pseudo- urbanization» characteristic of the Soviet economic and social system, superimposed on the process of «natural» urbanization. By natural urbanization we mean the process related to economic development and to the natural difference between rural and urban ways of life. The specificity, the structural changes and the hierarchy of city functions shape the migration flows conditioned by natural urbanization. «Pseudo-urbanization» points to «the scum» of the process, that may complete the economic and socially conditioned urbanization. The «pseudo-urbanization» is generated by a disproportionate development of the country's economic structure (hypertrophie share of industry; economic and political reforms have triggered off a massive flow of the peasantry towards the cities, related not with the rising but with the lowering of labour efficiency in agriculture, with impoverishment of the countryside and hence with the urge towards the centres of relative well-being), and by the territorial inequalities in standards of living, artificially created and maintained by the institution of passports and registration.

The suburbanization of population cannot be observed in the MCR. The centripetal tendencies mentioned above resulted in rapid growth of Moscow and its suburbs, as well as in some stagnation of its periphery. Thus Moscow agglomeration is now in the first stage of development, the stage of «crawling» concentration where centrifugal forces are very weak. This situation will last as long as the barrier in terms of standards of living exists between Moscow and Moscow oblast.

Conclusions

This study has reaffirmed the general lack of suburbanization in the Soviet cities. Some signs of suburbanization like the

transfer of some activities from Moscow to the suburbs, the concentration of population in towns and villages near the central

city and commuting, differ significantly pie and firms will emancipate, only if the from the Western cities. The process of ur- existing political and economic system in banization will take its normal course, peo- the USSR is dismantled.

Argumenty i facty, 1988, N47, p. 2 Argumenty i facty, 1988, N50, p. 3

GLUSHKOVA V.G. Questions of Interrelated Settlement in Moscow and the Moscow Region, Problems of Geography, vol. 131, Moscow, 1988, pp. 40-56.

GRITSAY O.V. Western Europe : Regional Contrasts at the New Stage of Scientific-Technological Progress, Moscow, 1988, 148 p.

Moscow in Figures. 1980, Moscow, 1981, 220 p. Moscow in Figures. 1985, Moscow, 1986, 240 p.

National Economy of Moscow Oblast. 1981-1985, Moscow, 1986, 271 p.

National Economy of the ussr. 1985, Moscow, 1986, 421 p. Yearbook of Labour Statistics. 1987, Geneva, 1987, 960 p.

Moscow Capital Region: Territorial Structure and Natural Environment, Moscow, 1988, 321 p.

(1) Limiters are unskilled workers, hired in an organised way by Moscow firms; after working there for several years of working they get the right to register

their passports and to take up their residence in Moscow.