Alternative Assessment Models: A Search for New Tools for Admission to Higher Education Howard T. Everson The College Board Presentation at the Conference Rethinking the SAT in University Admissions University of California, Santa Barbara, November 16-17, Santa Barbara, CA

Why Search Now?  Continuing Pressure to Reform Schools in the US—with Test Driven Accountability Approaches  Technological Advances  Computer-Based Testing  Portfolios  Standards-Based Assessments  Influence of Cognitive Psychology  New Theories of Human Learning  New Theories of Developing Abilities

A Palette of Human Abilities  Aptitudes: Verbal reasoning, mathematical reasoning--- generalized learning abilities  Achievement: Cognitive/Academic, Subject-Matter Related, Performances  Non-Cognitive Abilities: Attitudes, Personality Factors, Documented Accomplishments, and Learning & Study Strategies  Developing Abilities: Practical and Creative Forms of Intellective Competence (R. Sternberg, E. Gordon)

The College Board’s Search Strategy lOur Framework Draws on the Work of Bok- Gardner Commission on New Possibilities Abilities for the SAT lDevelop measures that blend aptitude & achievement lExplore non-cognitive measures—attitudes, personality lExamine alternative notions of ability and intellective competence lExplore the Use of Computer-Based Test Methods lMaintain Psychometric Quality of Assessments lValidity: Construct, Predictive, Instructionally Appropriate lReliability lOperational Feasibility

Why Are We Concerned With Strategic Learning? lWhat Is Strategic Learning? The skills, attitudes, beliefs, behaviors, and ways of thinking that typify successful learners (Weinstein & Hume, 1998). lThe Components of Strategic Learning A Model of Strategic Learning Nature of Learning Activities Teacher Beliefs & Expectations Social Context & Support XSkill, Will & Self-Regulation

Assessing Learning & Study Strategies: The LASSI-HS lThe LASSI-HS: The High School version of Learning & Study Strategies Inventory is a 76 item self-report instrument. lThe LASSI-HS is both diagnostic and prescriptive and includes 10 subscales: 1. Attitudes About School 2. Motivation 3. Time Management 4. Anxiety About Learning 5. Concentration 6. Information Processing 7. Selecting Main Ideas 8. Use of Study Aids 9. Use of Self Testing10. Test Taking Strategies

Assessing Cognitive Abilities with the PSAT: Verbal & Mathematical Reasoning Measures lThe PSAT/NMSQT (1996, College Board) Measures Verbal and Mathematical Reasoning lVerbal Reasoning Measures include: Sentence Completion: Logic & Vocabulary Analogical Reasoning Critical Reading Mathematical Reasoning Measures include: Mathematical Problem Solving Quantitative Comparisons & Grid-In Responses Measures of Reasoning, Math Concepts, & Math Knowledge

Who Took Part In The Study? lParticipants were 1,650 10th & 11th Grade Students from 10 high schools across the U.S. l52 % 10th Graders (N = 859) l48% 11th Graders (N = 791) l60% Female & 40% Male lAverage PSAT Scores & GPAs By Gender MALESFEMALES Math Verbal H.S. GPA* * Scale

Results on LASSI-HS Subscales LASSI-HS ScalesMean Score Percentile (%) Attitude Motivation Time Mgmt Anxiety Concentration Info. Processing Main Ideas Study Aids Self Testing Test Taking

Correlations of LASSI-HS, with PSAT V & M, and GPA LASSI-HSPSAT- MPSAT-VGPA Attitude Motivation Time Mgmt Anxiety Concentration Info. Process Main Ideas Study Aids Self Testing Test Taking

First Order Factor Analysis of the LASSI-HS Subscales SUBSCALES FACTOR 1 FACTOR 2 Attitude Motivation Time Mgmt Anxiety Concentration Info. Process Main Ideas Study Aids Self Testing Test Taking (Note: % of Variance = 66.7)

Correlations Among First Order Factor Scores of the LASSI-HS, PSAT V & M, and GPA LASSI-F1 LASSI-F2 PSAT- M PSAT-V GPA F F PSAT-M PSAT-V GPA

Results of Regression Analyses Entire Sample Dependent Variable = GPA R 2 Model 1: PSAT-M + PSAT- V.28 Model 2: LASSI F1 + LASSI F2.14 Model 3: PSAT-M + PSAT-V + LASSI F2 + LASSI F1.37

Results of Regression Analyses By Grade Level Grade 10 Grade 11 Dependent Variable = GPA R 2 R 2 Model 1: PSAT-M + PSAT- V Model 2: LASSI F1 + LASSI F Model 3: PSAT-M + PSAT-V + LASSI F2 + LASSI F

Conclusions & Implications lLASSI-HS Measures Add Information to PSAT lPossible to Use LASSI-HS in Diagnostic and Placement Testing Framework lLearning Strategies Are Developing Skills lLASSI-HS Can Inform Students of Learning Skills Promote Self-Reflection of Learning Strategies Embed Strategy Training and Use In Classroom Encourage Learners to Take Control of Learning Promote Students’ Mastery Through Feedback Implement Strategies for Self-Regulation of Learning