CHI TIẾT NGHIÊN CỨU …
Tiêu đề
Examining the Psychometric Properties of a New Integrative Learning Scale
Tác giả
Youngerman E.; Dahl L.S.; Mayhew M.J.
Năm xuất bản
2021
Source title
Research in Higher Education
Số trích dẫn
3
DOI
10.1007/s11162-021-09623-1
Liên kết
Tóm tắt
Integrative learning is the ability to connect, apply, and/or synthesize. A highly valued skill for the knowledge economy and combating false narratives, integrative learning represents the cognitive heart of the liberal arts, demonstrating students’ ability to make interdisciplinary connections and apply their learning to their lives and the outside world. But integrative learning has not been successfully measured. This study piloted the 7-item Integrative Learning Scale. Data from 1,919 college students at three institutions were analyzed using Rasch modeling. The results of this study suggest that integrative learning can be measured and the Integrative Learning Scale has strong psychometric properties for doing so. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
Từ khóa
Integrative learning; Rasch modeling; Reliability; Validity
Tài liệu tham khảo
Andrich D., A rating formulation for ordered response categories, Psychometrika, 43, 4, pp. 561-573, (1978); Standards for Educational and Psychological Testing, (2014); Greater Expectations: A New Vision for Learning as a Nation Goes to College. Washington, DC: AAC&U, (2002); Integrative Learning VALUE Rubric, (2010); Universities, (2010); Barber J.P., Integration of learning: A grounded theory analysis of college students' learning, American Educational Research Journal., 49, 3, pp. 590-617, (2012); Barber J.P., Integration of learning model: How college students integrate learning, New Directions for Higher Education, 165, pp. 7-17, (2014); Barber J.P., Facilitating the integration of learning: Five research-based practices to help college students connect learning across disciplines and lives experience, (2020); Baxter Magolda M., Evolution of a Constructivist Conceptualization of Epistemological Reflection, Educational Psychologist, 39, 1, pp. 31-42, (2004); Baxter Magolda M., The activity of meaning making: A holistic perspective on college student development, Journal of College Student Development, 50, 6, pp. 621-636, (2009); Benjamini Y., Hochberg Y., Controlling the false discovery rate: A practical and powerful approach to multiple testing, Journal of the Royal Statistical Society, 57, 1, pp. 289-300, (1995); Boning K., Coherence in general education: A historical look, Journal of General Education, 56, 1, pp. 1-16, (2007); Boone W.J., Staver J.R., Yale M.S., Rasch analysis in the human sciences, (2014); Brint S., Proctor K., Murphy S.P., Turk-Bicakci L., Hanneman R.A., General education models: Continuity and change in the U.S. undergraduate curriculum, 1975–2000, Journal of Higher Education, 80, 6, pp. 605-642, (2009); Brown T.A., Confirmatory factor analysis for applied research, (2015); Carmines E.G., Zeller R.A., Reliability and validity assessment, (1979); Carnegie Foundation for the Advancement of Teaching (CFAT), (2004); Cohen J., Statistical power analysis for the behavioral sciences, (1988); Cortina J.M., What is coefficient alpha? An examination of theory and applications, Journal of Applied Psychology, 78, 1, pp. 98-104, (1993); Cronbach L.J., Coefficient alpha and the internal structure of tests, Psychometrika, 16, 3, pp. 297-334, (1951); Cronbach L.J., Meehl P.E., Construct validity in psychological tests, Psychological Bulletin, 52, 4, pp. 281-302, (1955); DeVellis R., Scale development: Theory and applications, (2017); Gadermann A.M., Guhn M., Zumbo B.D., Estimating ordinal reliability for Likert-type and ordinal item response data: A conceptual, empirical, and practical guide, Practical Assessment, Research & Evaluation, 17, 3, pp. 1-13, (2012); Hayton J.C., Allen D.G., Scarpello V., Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis, Organizational Research Methods, 7, pp. 191-205, (2004); Validity and Limitations of College Student Self-Report Data: New Directions for Institutional Research, Number 150, 110, (2011); Hopkins K.D., Educational and psychological measurement and evaluation, (1998); Horowitz H., Alma mater: Design and experience in the women’s colleges from their Nineteenth century beginnings to the 1930s, (1984); Hu L.T., Bentler P.M., Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives, Structural Equation Modeling: A Multidisciplinary Journal, 6, 1, pp. 1-55, (1999); Huber M., Hutchings P., Integrative learning: Mapping the terrain, (2004); Inkelas K., Vogt K., Longerbeam S., Owen J., Johnson D., Measuring outcomes of living-learning programs: Examining college environments and student learning and development, Journal of General Education, 55, 1, pp. 40-76, (2006); Inkelas K., (2008), (2007); Kegan R., In over our heads: The mental demands of modern life, (1994); Kerlinger F., Foundations of behavioral research, (1973); King P., Kitchener K., Developing reflective judgment: Understanding and promoting intellectual growth and critical thinking in adolescents and adults, (1994); King P., Kitchener K., Reflective judgment: Theory and research on the development of epistemic assumptions through adulthood, Educational Psychologist, 39, 1, pp. 5-18, (2004); Klein J., Interdisciplinarity: History, theory, and practice, (1990); Kolb D., Learning styles and disciplinary differences, The modern American college, pp. 232-255, (1981); Laird T.F.N., Seifert T.A., Pascarella E.T., Mayhew M.J., Blaich C.F., Deeply Affecting First-Year Students’ Thinking: Deep Approaches to Learning and Three Dimensions of Cognitive Development, The Journal of Higher Education, 85, 3, pp. 402-432, (2014); Lardner E., Malnarich G., When faculty assess integrative learning, Change, 41, 5, pp. 29-35, (2010); Lattuca L., Creating interdisciplinarity: Interdisciplinary research and teaching among college and university faculty, (2001); Linacre J.M., What do infit and outfit, mean-square and standardized mean?, Rasch Measurement Transactions, 16, 2, (2002); Linacre J.M., Winsteps® Rasch measurement computer program user’s guide, (2013); Linacre J.M., A user’s guide to WINSTEPS MINISTEP Rasch-model computer programs, (2018); Ludlow L.H., Haley S.M., Rasch model logits: Interpretation, use, and transformation, Educational and Psychological Measurement, 55, 6, pp. 967-975, (1995); Maydeu-Olivares A., Coffman D., Hartmann W., Asymptotically distribution-free (ADF) interval estimation of coefficient alpha: Correction, Psychological Methods, 12, 4, (2007); Mayhew M.J., Seifert T.A., Pascarella E.T., Nelson Laird T.F., Blaich C.F., Going deep into mechanisms for moral reasoning growth: How deep learning approaches affect moral reasoning development for first-year students, Research in Higher Education, 53, pp. 26-46, (2012); Meiklejohn A., The Experimental College, (1932); Messick S., Meaning and values in test validation: The science and ethics of assessment, Educational Researcher, 18, 2, pp. 5-11, (1989); Messick S., Validity of psychological assessment: Validation of inferences from persons' responses and performances as scientific inquiry into score meaning, American Psychologist, 50, 9, (1995); (2020); Survey Instrument, (2015); Nunnally J., Educational measurement and evaluation, (1972); Nunnally J.C., Psychometric theory, (1978); O'Neill N., Promising practices for personal and social responsibility: Findings from a national research collaborative, (2012); Pascarella E., Terenzini P., How college affects students: Findings and insights from twenty years of research, (1991); Pascarella E., Et al., Methodological Report for the Wabash National Study of Liberal Arts Education, (2007); Peet M., Lonn S., Gurin P., Boyer K., Matney M., Marra T., Daley A., Fostering integrative knowledge through ePortfolios, International Journal of Eportfolio, 1, 1, pp. 11-31, (2011); Perkins D., Salomon G., Transfer of learning, International Encyclopedia of Education, (1992); Pierson G., Yale: The university college 1921–1937, (1955); Pike G.R., Kuh G.D., First- and second-generation college students: A comparison of their engagement and intellectual development, Journal of Higher Education, 76, 3, pp. 276-301, (2005); Porter S.R., Do college student surveys have any validity?, The Review of Higher Education, 35, 1, pp. 45-76, (2011); Rhodes T., Finley A., Using the VALUE rubrics for improvement of learning and authentic assessment, (2013); Rupp A., Koh K., Zumbo B.D., What is the impact on exploratory factor analysis results of a polychoric correlation matrix from LISREL/PRELIS and EQS when some respondents are not able to follow the rating scale, Paper Presented at the Annual Meeting of the American Educational Research Association, (2003); Tabachnick B.G., Fidell L.S., Using multivariate statistics, (2001); Taber K.S., The use of Cronbach’s alpha when developing and reporting research instruments in science education, Research in Science Education, 48, 6, pp. 1273-1296, (2018); Thorndike E.L., A constant error in psychological ratings, Journal of Applied Psychology, 4, 1, pp. 25-29, (1920); Thurstone L.L., Attitudes can be measured, American Journal of Sociology, 33, 4, pp. 529-554, (1928); Wentland E.J., Smith K.W., Survey responses: An evaluation of their validity, (1993); Wineburg S., McGrew S., Breakstone J., Ortega T., Evaluating Information: The Cornerstone of Civic Online Reasoning, Stanford History Education Group, (2016); Wolfe E.W., Smith J.E., Instrument development tools and activities for measure validation using Rasch models: Part II - Validation activities, Journal of Applied Measurement, 8, 2, pp. 204-234, (2007); Wright B.D., Sample-Free Test Calibration and Person Measurement. Proceedings of the 1967 Invitational Conference on Testing Problems, (1967); Wright B.D., Stone M., Best test design, (1979); Youngerman E., Integrative Learning in Award-Winning Student Writing: A Grounded Theory Analysis. (Publication No. 10279690) [Doctoral Dissertation, (2017); Youngerman E., Integrative learning in award-winning student writing: A grounded theory analysis, AERA Open, 4, 3, pp. 1-13, (2018); Youngerman E., Culver K., Problem-based learning (PBL): Real-world applications to foster (inter)disciplinary learning and integration, New Directions for Higher Education, 2019, 188, pp. 23-32, (2019); Zumbo B.D., Gadermann A.M., Zeisser C., Ordinal versions of coefficient alpha and theta for Likert rating scales, Journal of Modern Applied Statistical Methods, 6, pp. 21-29, (2007); Zumbo B., Rupp A., Responsible modeling of measurement data for appropriate inferences: Important advances in reliability and validity theory, The SAGE Handbook of Quantitative Methodology for the Social Sciences, pp. 73-92, (2004)
Nơi xuất bản
Springer Science and Business Media B.V.
Hình thức xuất bản
Article
Open Access
Nguồn
Scopus