Laura Young

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Laura K. Young

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Biography

Temple University - Education

Research Scientist at Temple University
Higher Education
Laura
Young
Pottstown, Pennsylvania
Expert in numerical cognition and learning who is dedicated to innovative pedagogy and infusing research-based practices into real-world settings. Exceptional history of designing and assessing education research studies and materials, and their effectiveness. Strong ability to compile and analyze data. Quick learner and multi-tasker who works well in leadership roles and as part of a team, yet is able to self-motivate. Skilled in synthesizing complex ideas and concepts into essential and useful information. Excellent verbal and written communication skills.

Broad Research Interests: Development of mathematic cognition and learning, predicting future knowledge, informal learning, educational interventions, classroom research, instructional material design, translational research

Experience

  • Temple University

    Graduate Research Assistant

    • Designed novel research studies and managed multiple project simultaneously
    • Analyzed finings and summarized key points quickly and concisely
    • Shared findings at national and international conferences, and through peer-reviewed scholarly journal articles and book chapters

  • Temple University

    Instructor

    Child Development: Birth through Nine.

  • Temple University

    Postdoctoral Research Fellow

    • Contribute to and lead multiple research projects simultaneously, including designing and revising research protocols based on synthesizing materials from a variety of sources
    • Collaborate with several research associates of various seniority and mentor junior researchers
    • Create complex databases, analyzed data, and summarize data findings for brief reports, presentations, and journal publications
    • Develop and deliver presentations on a variety of topics for audiences from 5-50 people at local, national, and international meetings and conferences

  • Temple University

    Instructor

    Educational Psychology 2325: Statistics for Decision Making

    • Delivered lectures and led discussions to improve students understanding of challenging statistics content
    • Developed all course materials (exams, assignments, and lectures), selected course readings, and designed lessons to engage students with course content
    • Developed strategies to teach students how to make decisions based on statistical findings, and how to disseminate these findings to the public
    • Evaluated student progress and responded to student feedback to improve learning
    • Met with students outside of class hours to resolve difficulties, counseled students on their academic progress, and managed concerns of academic integrity

  • Temple University

    Research Scientist

    Laura worked at Temple University as a Research Scientist

  • Penn State University

    Teaching Assistant

    Laura worked at Penn State University as a Teaching Assistant

  • Penn State University

    Instructor

    Human Development and Family Studies 429: Advanced Child Development
    Psychology 410: Child Development

  • TD Bank

    Bank Teller II

    Laura worked at TD Bank as a Bank Teller II

  • Penn State Brandywine Child Development Lab

    Undergraduate Research Assistant

    Laura worked at Penn State Brandywine Child Development Lab as a Undergraduate Research Assistant

Education

  • Temple University

    Master's Degree

    Master of Education, Educational Psychology

  • Temple University

    Doctor of Philosophy (Ph.D.)

    Educational Psychology

  • Temple University

    Graduate Research Assistant


    • Designed novel research studies and managed multiple project simultaneously • Analyzed finings and summarized key points quickly and concisely • Shared findings at national and international conferences, and through peer-reviewed scholarly journal articles and book chapters

  • Temple University

    Instructor


    Child Development: Birth through Nine.

  • Temple University

    Postdoctoral Research Fellow


    • Contribute to and lead multiple research projects simultaneously, including designing and revising research protocols based on synthesizing materials from a variety of sources • Collaborate with several research associates of various seniority and mentor junior researchers • Create complex databases, analyzed data, and summarize data findings for brief reports, presentations, and journal publications • Develop and deliver presentations on a variety of topics for audiences from 5-50 people at local, national, and international meetings and conferences

  • Temple University

    Instructor


    Educational Psychology 2325: Statistics for Decision Making • Delivered lectures and led discussions to improve students understanding of challenging statistics content • Developed all course materials (exams, assignments, and lectures), selected course readings, and designed lessons to engage students with course content • Developed strategies to teach students how to make decisions based on statistical findings, and how to disseminate these findings to the public • Evaluated student progress and responded to student feedback to improve learning • Met with students outside of class hours to resolve difficulties, counseled students on their academic progress, and managed concerns of academic integrity

  • Temple University

    Research Scientist



  • Penn State University

    BS

    Human Development and Family Studies

  • Penn State University

    Teaching Assistant



  • Penn State University

    Instructor


    Human Development and Family Studies 429: Advanced Child Development Psychology 410: Child Development

Publications

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • Simple Practice Doesn’t Necessarily Make Perfect: Evidence from the Worked Example Effect

    Policy Insights from Behavioral and Brain Sciences

    Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into practice sessions in Science, Technology, Engineering, and Mathematics (STEM) classrooms. Research in scientific laboratories and real-world classrooms has also identified a number of methods for utilizing worked examples in lessons, including fading the examples; prompting self-explanation of the examples, including incorrect examples; and providing opportunities for students to compare multiple examples. Each of these methods has been shown to lend itself well to particular types of learning goals. Implications for education policy are discussed, including rethinking the ways in which STEM textbooks are constructed, finding ways to support educators in recognizing and implementing effective cognitive science–based pedagogical techniques, and changing the climate in classrooms to include the perception of errors as a functional part of the learning process.

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • Simple Practice Doesn’t Necessarily Make Perfect: Evidence from the Worked Example Effect

    Policy Insights from Behavioral and Brain Sciences

    Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into practice sessions in Science, Technology, Engineering, and Mathematics (STEM) classrooms. Research in scientific laboratories and real-world classrooms has also identified a number of methods for utilizing worked examples in lessons, including fading the examples; prompting self-explanation of the examples, including incorrect examples; and providing opportunities for students to compare multiple examples. Each of these methods has been shown to lend itself well to particular types of learning goals. Implications for education policy are discussed, including rethinking the ways in which STEM textbooks are constructed, finding ways to support educators in recognizing and implementing effective cognitive science–based pedagogical techniques, and changing the climate in classrooms to include the perception of errors as a functional part of the learning process.

  • Algebra Performance and Motivation Differences for Students with Learning Disabilities and Students of Varying Achievement Levels

    Contemporary Educational Psychology

    Prior research has documented differences in both performance and motivation between students with learning disabilities (LD) and non-learning disabled (non-LD) students. However, few studies have conducted a finer grained analysis comparing students with LD with nondisabled students of varying achievement levels. The present study examines differences between LD, low-achieving, average-achieving, and high-achieving adolescents on algebra performance and readiness, motivational constructs (competence expectancy, interest, and goal orientation in mathematics), and the discrepancy between students' competence and their perceptions of their own competence. Results indicate that while students with LD may demonstrate lower algebra readiness and algebra achievement and more inaccurate judgments of their own competence compared with the whole non-LD sample, critical differences in performance and motivation were most evident between high-achieving and low-achieving students, not students with learning disabilities.

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • Simple Practice Doesn’t Necessarily Make Perfect: Evidence from the Worked Example Effect

    Policy Insights from Behavioral and Brain Sciences

    Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into practice sessions in Science, Technology, Engineering, and Mathematics (STEM) classrooms. Research in scientific laboratories and real-world classrooms has also identified a number of methods for utilizing worked examples in lessons, including fading the examples; prompting self-explanation of the examples, including incorrect examples; and providing opportunities for students to compare multiple examples. Each of these methods has been shown to lend itself well to particular types of learning goals. Implications for education policy are discussed, including rethinking the ways in which STEM textbooks are constructed, finding ways to support educators in recognizing and implementing effective cognitive science–based pedagogical techniques, and changing the climate in classrooms to include the perception of errors as a functional part of the learning process.

  • Algebra Performance and Motivation Differences for Students with Learning Disabilities and Students of Varying Achievement Levels

    Contemporary Educational Psychology

    Prior research has documented differences in both performance and motivation between students with learning disabilities (LD) and non-learning disabled (non-LD) students. However, few studies have conducted a finer grained analysis comparing students with LD with nondisabled students of varying achievement levels. The present study examines differences between LD, low-achieving, average-achieving, and high-achieving adolescents on algebra performance and readiness, motivational constructs (competence expectancy, interest, and goal orientation in mathematics), and the discrepancy between students' competence and their perceptions of their own competence. Results indicate that while students with LD may demonstrate lower algebra readiness and algebra achievement and more inaccurate judgments of their own competence compared with the whole non-LD sample, critical differences in performance and motivation were most evident between high-achieving and low-achieving students, not students with learning disabilities.

  • Evidence for Cognitive Science Principles that Impact Learning in Mathematics

    In D.C. Geary, D. Berch, R. Oschendorf, & K.M. Koepke (Eds.) Mathematical Cognition and Learning Volume 3: Acquisition of Complex Arithmetic Skills and Higher-Order Mathematics Concepts (pp. 297-325)

    Numerous issues with mathematics education in the United States have led to repeated calls for instruction to align more fully with evidence-based practices. The field of cognitive science has identified and tested a number of principles for improving learning, but many of these principles have not yet been used to their fullest to improve mathematics learning in U.S. classrooms. In this chapter, we describe eight principles that may have particular promise for mathematics education: Abstract and concrete representations, analogical comparison, feedback, error reflection, scaffolding, distributed practice, interleaved practice, and worked examples. For each principle, we review laboratory and classroom evidence related to benefits for mathematics learning and identify priorities for future research.

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • Simple Practice Doesn’t Necessarily Make Perfect: Evidence from the Worked Example Effect

    Policy Insights from Behavioral and Brain Sciences

    Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into practice sessions in Science, Technology, Engineering, and Mathematics (STEM) classrooms. Research in scientific laboratories and real-world classrooms has also identified a number of methods for utilizing worked examples in lessons, including fading the examples; prompting self-explanation of the examples, including incorrect examples; and providing opportunities for students to compare multiple examples. Each of these methods has been shown to lend itself well to particular types of learning goals. Implications for education policy are discussed, including rethinking the ways in which STEM textbooks are constructed, finding ways to support educators in recognizing and implementing effective cognitive science–based pedagogical techniques, and changing the climate in classrooms to include the perception of errors as a functional part of the learning process.

  • Algebra Performance and Motivation Differences for Students with Learning Disabilities and Students of Varying Achievement Levels

    Contemporary Educational Psychology

    Prior research has documented differences in both performance and motivation between students with learning disabilities (LD) and non-learning disabled (non-LD) students. However, few studies have conducted a finer grained analysis comparing students with LD with nondisabled students of varying achievement levels. The present study examines differences between LD, low-achieving, average-achieving, and high-achieving adolescents on algebra performance and readiness, motivational constructs (competence expectancy, interest, and goal orientation in mathematics), and the discrepancy between students' competence and their perceptions of their own competence. Results indicate that while students with LD may demonstrate lower algebra readiness and algebra achievement and more inaccurate judgments of their own competence compared with the whole non-LD sample, critical differences in performance and motivation were most evident between high-achieving and low-achieving students, not students with learning disabilities.

  • Evidence for Cognitive Science Principles that Impact Learning in Mathematics

    In D.C. Geary, D. Berch, R. Oschendorf, & K.M. Koepke (Eds.) Mathematical Cognition and Learning Volume 3: Acquisition of Complex Arithmetic Skills and Higher-Order Mathematics Concepts (pp. 297-325)

    Numerous issues with mathematics education in the United States have led to repeated calls for instruction to align more fully with evidence-based practices. The field of cognitive science has identified and tested a number of principles for improving learning, but many of these principles have not yet been used to their fullest to improve mathematics learning in U.S. classrooms. In this chapter, we describe eight principles that may have particular promise for mathematics education: Abstract and concrete representations, analogical comparison, feedback, error reflection, scaffolding, distributed practice, interleaved practice, and worked examples. For each principle, we review laboratory and classroom evidence related to benefits for mathematics learning and identify priorities for future research.

  • Misconceptions and Learning Algebra

    In S. Stewart (Ed.) …And the Rest is Just Algebra (pp.63-78)

    Rather than exclusively focus on mastery of procedural skills, mathematics educators are encouraged to cultivate conceptual understanding in their classrooms. However, mathematics learners hold many faulty conceptual ideas—or misconceptions—at various points in the learning process. In the present chapter, we first describe the common misconceptions that students hold when learning algebra. We then explain why these misconceptions are problematic and detail a potential solution with the capability to help students build correct conceptual knowledge while they are learning new procedural skills. Finally, we discuss other potential implications from the existence of algebraic misconceptions which require further study. In general, preventing and remediating algebraic misconceptions may be necessary for increasing student success in algebra and, subsequently, more advanced mathematics classes.

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • Simple Practice Doesn’t Necessarily Make Perfect: Evidence from the Worked Example Effect

    Policy Insights from Behavioral and Brain Sciences

    Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into practice sessions in Science, Technology, Engineering, and Mathematics (STEM) classrooms. Research in scientific laboratories and real-world classrooms has also identified a number of methods for utilizing worked examples in lessons, including fading the examples; prompting self-explanation of the examples, including incorrect examples; and providing opportunities for students to compare multiple examples. Each of these methods has been shown to lend itself well to particular types of learning goals. Implications for education policy are discussed, including rethinking the ways in which STEM textbooks are constructed, finding ways to support educators in recognizing and implementing effective cognitive science–based pedagogical techniques, and changing the climate in classrooms to include the perception of errors as a functional part of the learning process.

  • Algebra Performance and Motivation Differences for Students with Learning Disabilities and Students of Varying Achievement Levels

    Contemporary Educational Psychology

    Prior research has documented differences in both performance and motivation between students with learning disabilities (LD) and non-learning disabled (non-LD) students. However, few studies have conducted a finer grained analysis comparing students with LD with nondisabled students of varying achievement levels. The present study examines differences between LD, low-achieving, average-achieving, and high-achieving adolescents on algebra performance and readiness, motivational constructs (competence expectancy, interest, and goal orientation in mathematics), and the discrepancy between students' competence and their perceptions of their own competence. Results indicate that while students with LD may demonstrate lower algebra readiness and algebra achievement and more inaccurate judgments of their own competence compared with the whole non-LD sample, critical differences in performance and motivation were most evident between high-achieving and low-achieving students, not students with learning disabilities.

  • Evidence for Cognitive Science Principles that Impact Learning in Mathematics

    In D.C. Geary, D. Berch, R. Oschendorf, & K.M. Koepke (Eds.) Mathematical Cognition and Learning Volume 3: Acquisition of Complex Arithmetic Skills and Higher-Order Mathematics Concepts (pp. 297-325)

    Numerous issues with mathematics education in the United States have led to repeated calls for instruction to align more fully with evidence-based practices. The field of cognitive science has identified and tested a number of principles for improving learning, but many of these principles have not yet been used to their fullest to improve mathematics learning in U.S. classrooms. In this chapter, we describe eight principles that may have particular promise for mathematics education: Abstract and concrete representations, analogical comparison, feedback, error reflection, scaffolding, distributed practice, interleaved practice, and worked examples. For each principle, we review laboratory and classroom evidence related to benefits for mathematics learning and identify priorities for future research.

  • Misconceptions and Learning Algebra

    In S. Stewart (Ed.) …And the Rest is Just Algebra (pp.63-78)

    Rather than exclusively focus on mastery of procedural skills, mathematics educators are encouraged to cultivate conceptual understanding in their classrooms. However, mathematics learners hold many faulty conceptual ideas—or misconceptions—at various points in the learning process. In the present chapter, we first describe the common misconceptions that students hold when learning algebra. We then explain why these misconceptions are problematic and detail a potential solution with the capability to help students build correct conceptual knowledge while they are learning new procedural skills. Finally, we discuss other potential implications from the existence of algebraic misconceptions which require further study. In general, preventing and remediating algebraic misconceptions may be necessary for increasing student success in algebra and, subsequently, more advanced mathematics classes.

  • Student Magnitude Knowledge of Negative Numbers

    Journal of Numerical Cognition

    Numerous studies have demonstrated the relevance of magnitude estimation skills for mathematical proficiency, but little research has explored magnitude estimation with negative numbers. In two experiments the current study examined middle school students’ magnitude knowledge of negative numbers with number line tasks. In Experiment 1, both 6th (n = 132) and 7th grade students (n = 218) produced linear representations on a -10,000 to 0 scale, but the 7th grade students’ estimates were more accurate and linear. In Experiment 2, the 7th grade students also completed a -1,000 to 1,000 number line task; these results also indicated that students are linear for both negative and positive estimates. When comparing the estimates of negative and positive numbers, analyses illustrated that estimates of negative numbers are less accurate than those of positive numbers, but using a midpoint strategy improved negative estimates. These findings suggest that negative number magnitude knowledge follows a similar pattern to positive numbers, but the estimation performance of negatives lags behind that of positives.

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • Simple Practice Doesn’t Necessarily Make Perfect: Evidence from the Worked Example Effect

    Policy Insights from Behavioral and Brain Sciences

    Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into practice sessions in Science, Technology, Engineering, and Mathematics (STEM) classrooms. Research in scientific laboratories and real-world classrooms has also identified a number of methods for utilizing worked examples in lessons, including fading the examples; prompting self-explanation of the examples, including incorrect examples; and providing opportunities for students to compare multiple examples. Each of these methods has been shown to lend itself well to particular types of learning goals. Implications for education policy are discussed, including rethinking the ways in which STEM textbooks are constructed, finding ways to support educators in recognizing and implementing effective cognitive science–based pedagogical techniques, and changing the climate in classrooms to include the perception of errors as a functional part of the learning process.

  • Algebra Performance and Motivation Differences for Students with Learning Disabilities and Students of Varying Achievement Levels

    Contemporary Educational Psychology

    Prior research has documented differences in both performance and motivation between students with learning disabilities (LD) and non-learning disabled (non-LD) students. However, few studies have conducted a finer grained analysis comparing students with LD with nondisabled students of varying achievement levels. The present study examines differences between LD, low-achieving, average-achieving, and high-achieving adolescents on algebra performance and readiness, motivational constructs (competence expectancy, interest, and goal orientation in mathematics), and the discrepancy between students' competence and their perceptions of their own competence. Results indicate that while students with LD may demonstrate lower algebra readiness and algebra achievement and more inaccurate judgments of their own competence compared with the whole non-LD sample, critical differences in performance and motivation were most evident between high-achieving and low-achieving students, not students with learning disabilities.

  • Evidence for Cognitive Science Principles that Impact Learning in Mathematics

    In D.C. Geary, D. Berch, R. Oschendorf, & K.M. Koepke (Eds.) Mathematical Cognition and Learning Volume 3: Acquisition of Complex Arithmetic Skills and Higher-Order Mathematics Concepts (pp. 297-325)

    Numerous issues with mathematics education in the United States have led to repeated calls for instruction to align more fully with evidence-based practices. The field of cognitive science has identified and tested a number of principles for improving learning, but many of these principles have not yet been used to their fullest to improve mathematics learning in U.S. classrooms. In this chapter, we describe eight principles that may have particular promise for mathematics education: Abstract and concrete representations, analogical comparison, feedback, error reflection, scaffolding, distributed practice, interleaved practice, and worked examples. For each principle, we review laboratory and classroom evidence related to benefits for mathematics learning and identify priorities for future research.

  • Misconceptions and Learning Algebra

    In S. Stewart (Ed.) …And the Rest is Just Algebra (pp.63-78)

    Rather than exclusively focus on mastery of procedural skills, mathematics educators are encouraged to cultivate conceptual understanding in their classrooms. However, mathematics learners hold many faulty conceptual ideas—or misconceptions—at various points in the learning process. In the present chapter, we first describe the common misconceptions that students hold when learning algebra. We then explain why these misconceptions are problematic and detail a potential solution with the capability to help students build correct conceptual knowledge while they are learning new procedural skills. Finally, we discuss other potential implications from the existence of algebraic misconceptions which require further study. In general, preventing and remediating algebraic misconceptions may be necessary for increasing student success in algebra and, subsequently, more advanced mathematics classes.

  • Student Magnitude Knowledge of Negative Numbers

    Journal of Numerical Cognition

    Numerous studies have demonstrated the relevance of magnitude estimation skills for mathematical proficiency, but little research has explored magnitude estimation with negative numbers. In two experiments the current study examined middle school students’ magnitude knowledge of negative numbers with number line tasks. In Experiment 1, both 6th (n = 132) and 7th grade students (n = 218) produced linear representations on a -10,000 to 0 scale, but the 7th grade students’ estimates were more accurate and linear. In Experiment 2, the 7th grade students also completed a -1,000 to 1,000 number line task; these results also indicated that students are linear for both negative and positive estimates. When comparing the estimates of negative and positive numbers, analyses illustrated that estimates of negative numbers are less accurate than those of positive numbers, but using a midpoint strategy improved negative estimates. These findings suggest that negative number magnitude knowledge follows a similar pattern to positive numbers, but the estimation performance of negatives lags behind that of positives.

  • Exploring the Relationship between Adolescents’ Interest in Algebra and Procedural Declines

    Proceedings of the 38th Annual Meeting of the Cognitive Science Society

    Algebra I is considered a gatekeeper course for higher education and high-paying jobs, yet many students find themselves struggling with learning it. Prior research links intrinsic motivation for learning math with mathematics achievement, particularly during adolescence. The current study measured middle school students’ interest in algebra and their procedural skills across the span of an algebra unit to determine whether students who show declines in algebraic problem-solving also show a decline in a particular type of intrinsic motivation – interest in algebra. Pretest and posttest scores were used to categorize participants into those who showed declines in problem-solving skills and those who did not. Of the overall sample (N = 367), a group of 25 students showed declining skills over the course of the unit. These students also showed significant declines in interest in mathematics from pre- to post-test in comparison to students who did not show procedural declines.

  • The Interaction of Worked-Examples/ Self-Explanation Prompts and Time on Algebra Conceptual Knowledge

    Proceedings of the 39th Annual Meeting of the Cognitive Science Society

    Success in Algebra I often predicts whether or not a student will pursue higher levels of mathematics and science. However, many students enter algebra holding persistent misconceptions that are difficult to eliminate, thus, hindering their ability to succeed in algebra. One way to address these misconceptions is to implement worked-examples and self-explanation prompts, which have been shown to improve students’ conceptual knowledge. However this effect seems to be greater after a delay. The current study sought to explore such time-related effects on algebra conceptual knowledge. In a year-long random-assignment study, students either studied worked-examples and answered self-explanation prompts (n = 132) or solved typical isomorphic problems (n = 140). A three-way mixed ANCOVA (pre-algebra knowledge x condition x time) found a significant condition by time effect. The growth of algebra conceptual knowledge was greater for students studying worked-examples than for those solving typical problems.

  • Simple Practice Doesn’t Necessarily Make Perfect: Evidence from the Worked Example Effect

    Policy Insights from Behavioral and Brain Sciences

    Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into practice sessions in Science, Technology, Engineering, and Mathematics (STEM) classrooms. Research in scientific laboratories and real-world classrooms has also identified a number of methods for utilizing worked examples in lessons, including fading the examples; prompting self-explanation of the examples, including incorrect examples; and providing opportunities for students to compare multiple examples. Each of these methods has been shown to lend itself well to particular types of learning goals. Implications for education policy are discussed, including rethinking the ways in which STEM textbooks are constructed, finding ways to support educators in recognizing and implementing effective cognitive science–based pedagogical techniques, and changing the climate in classrooms to include the perception of errors as a functional part of the learning process.

  • Algebra Performance and Motivation Differences for Students with Learning Disabilities and Students of Varying Achievement Levels

    Contemporary Educational Psychology

    Prior research has documented differences in both performance and motivation between students with learning disabilities (LD) and non-learning disabled (non-LD) students. However, few studies have conducted a finer grained analysis comparing students with LD with nondisabled students of varying achievement levels. The present study examines differences between LD, low-achieving, average-achieving, and high-achieving adolescents on algebra performance and readiness, motivational constructs (competence expectancy, interest, and goal orientation in mathematics), and the discrepancy between students' competence and their perceptions of their own competence. Results indicate that while students with LD may demonstrate lower algebra readiness and algebra achievement and more inaccurate judgments of their own competence compared with the whole non-LD sample, critical differences in performance and motivation were most evident between high-achieving and low-achieving students, not students with learning disabilities.

  • Evidence for Cognitive Science Principles that Impact Learning in Mathematics

    In D.C. Geary, D. Berch, R. Oschendorf, & K.M. Koepke (Eds.) Mathematical Cognition and Learning Volume 3: Acquisition of Complex Arithmetic Skills and Higher-Order Mathematics Concepts (pp. 297-325)

    Numerous issues with mathematics education in the United States have led to repeated calls for instruction to align more fully with evidence-based practices. The field of cognitive science has identified and tested a number of principles for improving learning, but many of these principles have not yet been used to their fullest to improve mathematics learning in U.S. classrooms. In this chapter, we describe eight principles that may have particular promise for mathematics education: Abstract and concrete representations, analogical comparison, feedback, error reflection, scaffolding, distributed practice, interleaved practice, and worked examples. For each principle, we review laboratory and classroom evidence related to benefits for mathematics learning and identify priorities for future research.

  • Misconceptions and Learning Algebra

    In S. Stewart (Ed.) …And the Rest is Just Algebra (pp.63-78)

    Rather than exclusively focus on mastery of procedural skills, mathematics educators are encouraged to cultivate conceptual understanding in their classrooms. However, mathematics learners hold many faulty conceptual ideas—or misconceptions—at various points in the learning process. In the present chapter, we first describe the common misconceptions that students hold when learning algebra. We then explain why these misconceptions are problematic and detail a potential solution with the capability to help students build correct conceptual knowledge while they are learning new procedural skills. Finally, we discuss other potential implications from the existence of algebraic misconceptions which require further study. In general, preventing and remediating algebraic misconceptions may be necessary for increasing student success in algebra and, subsequently, more advanced mathematics classes.

  • Student Magnitude Knowledge of Negative Numbers

    Journal of Numerical Cognition

    Numerous studies have demonstrated the relevance of magnitude estimation skills for mathematical proficiency, but little research has explored magnitude estimation with negative numbers. In two experiments the current study examined middle school students’ magnitude knowledge of negative numbers with number line tasks. In Experiment 1, both 6th (n = 132) and 7th grade students (n = 218) produced linear representations on a -10,000 to 0 scale, but the 7th grade students’ estimates were more accurate and linear. In Experiment 2, the 7th grade students also completed a -1,000 to 1,000 number line task; these results also indicated that students are linear for both negative and positive estimates. When comparing the estimates of negative and positive numbers, analyses illustrated that estimates of negative numbers are less accurate than those of positive numbers, but using a midpoint strategy improved negative estimates. These findings suggest that negative number magnitude knowledge follows a similar pattern to positive numbers, but the estimation performance of negatives lags behind that of positives.

  • Exploring the Relationship between Adolescents’ Interest in Algebra and Procedural Declines

    Proceedings of the 38th Annual Meeting of the Cognitive Science Society

    Algebra I is considered a gatekeeper course for higher education and high-paying jobs, yet many students find themselves struggling with learning it. Prior research links intrinsic motivation for learning math with mathematics achievement, particularly during adolescence. The current study measured middle school students’ interest in algebra and their procedural skills across the span of an algebra unit to determine whether students who show declines in algebraic problem-solving also show a decline in a particular type of intrinsic motivation – interest in algebra. Pretest and posttest scores were used to categorize participants into those who showed declines in problem-solving skills and those who did not. Of the overall sample (N = 367), a group of 25 students showed declining skills over the course of the unit. These students also showed significant declines in interest in mathematics from pre- to post-test in comparison to students who did not show procedural declines.

  • The Impact of Fraction Magnitude Knowledge on Algebra Performance and Learning

    Journal of Experimental Child Psychology

    Knowledge of fractions is thought to be crucial for success with algebra, but empirical evidence supporting this conjecture is just beginning to emerge. In the current study, Algebra 1 students completed magnitude estimation tasks on three scales (0–1 [fractions], 0–1,000,000, and 0–62,571) just before beginning their unit on equation solving. Results indicated that fraction magnitude knowledge, and not whole number knowledge, was especially related to students’ pretest knowledge of equation solving and encoding of equation features. Pretest fraction knowledge was also predictive of students’ improvement in equation solving and equation encoding skills. Students’ placement of unit fractions (e.g., those with a numerator of 1) was not especially useful for predicting algebra performance and learning in this population. Placement of non-unit fractions was more predictive, suggesting that proportional reasoning skills might be an important link between fraction knowledge and learning algebra.

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  • Laura Young-Sampson (30% Match)
    Instructional Faculty
    California State University - California State University

ECED 2101

4.5(1)

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