Students home alone—profiles of internal and external conditions associated with mathematics learning from home

• Sarah I. Hofer ^[2] ; Frank Reinhold ^[3] ; Marco Koch ^[1]
  1. [1] Saarland University

     Saarland University

     Regionalverband Saarbrücken, Alemania

     
  2. [2] Swiss Federal Institute of Technology in Zurich

     Swiss Federal Institute of Technology in Zurich

     Zürich, Suiza

     
  3. [3] Institute for Mathematics Education, University of Education Freiburg, Freiburg, Germany

  Mostrar afiliaciones +
• Localización: European journal of psychology of education, ISSN-e 1878-5174, ISSN 0256-2928, Vol. 38, Nº 1, 2023, págs. 333-366
• Idioma: inglés
• DOI: 10.1007/s10212-021-00590-w
• Texto completo no disponible (Saber más ...)
• Resumen

  • This study aims at describing differences in internal and external resources of students to handle mathematics learning from home. Based on data from N = 223 7th-grade secondary school students gathered via an online survey at the end of the first school year during the COVID-19 pandemic, we used latent profile analysis to identify student profiles defined by the internal factors perceived value and success of students’ math learning from home and the external factors family support and teacher support—all specifically related to home learning. A number of general learning conditions, comprising internal (e.g., sustained attention) and external factors (e.g., socioeconomic status), are included as outcome variables. The best-fitting four-profile solution suggests one profile with comparably unfavorable internal and external resources. About 35% of the students are assigned to that profile. The other three profiles show combinations of, relative to the sample, more and less promising specific home learning and general learning conditions suggesting that these students have different resources available in the face of learning mathematics from home.

• Referencias bibliográficas
  • Agasisti, T., & Longobardi, S. (2017). Equality of educational opportunities, schools’ characteristics and resilient students: An empirical...
  • Alexander, K. L., Entwisle, D. R., & Olson, L. S. (2001). Schools, achievement, and inequality: A seasonal perspective. Educational Evaluation...
  • Almutairi, M. (2021). The effects of parental involvement on student success in middle school. Academic Journal of Research and Scientific...
  • Andrew, A., Cattan, S., Costa Dias, M., Farquharson, C., Kraftman, L., Krutikova, S., Phimister, A., & Sevilla, A. (2020). Inequalities...
  • Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of...
  • Artino, A. R., & Stephens, J. M. (2006). Learning online: Motivated to self-regulate. Academic Exchange Quarterly, 10(4), 176–182.
  • Ashcraft, M. H., & Moore, A. M. (2009). Mathematics anxiety and the affective drop in performance. Journal of Psychoeducational Assessment,...
  • Asparouhov, T., & Muthén, B. (2014). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome...
  • Atteberry, A., & McEachin, A. (2019). School’s out: The role of summers in understanding achievement disparities. American Educational...
  • Axelrod, M. I., Zhe, E. J., Haugen, K. A., & Klein, J. A. (2009). Self-management of on-task homework behavior: A promising strategy for...
  • Bacci, S., Pandolfi, S., & Pennoni, F. (2014). A comparison of some criteria for states selection in the latent Markov model for longitudinal...
  • Bakk, Z., & Vermunt, J. K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Forthcoming in Structural...
  • Bansak, C., & Starr, M. (2021). Covid-19 shocks to education supply: How 200,000 U.S. households dealt with the sudden shift to distance...
  • Barkatsas, A. T., Kasimatis, K., & Gialamas, V. (2009). Learning secondary mathematics with technology: Exploring the complex interrelationship...
  • Baticulon, R. E., Sy, J. J., Alberto, N. R. I., Baron, M. B. C., Mabulay, R. E. C., Rizada, L. G. T., Tiu, C. J. S., Clarion, C. A., &...
  • Begeny, J. C., Codding, R. S., Wang, J., Hida, R. M., Patterson, S. L., Kessler, S., Fields-Turner, F., & Ramos, K. A. (2020). An analysis...
  • Bergey, B. W., Parrila, R. K., & Deacon, S. H. (2018). Understanding the academic motivations of students with a history of reading difficulty:...
  • Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning organic...
  • Blotenberg, I., & Schmidt-Atzert, L. (2019). Towards a process model of sustained attention tests. Journal of Intelligence, 7(1), 3. https://doi.org/10.3390/jintelligence7010003
  • Broadbent, J. (2017). Comparing online and blended learner’s self-regulated learning strategies and academic performance. The Internet and...
  • Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning...
  • Brühwiler, C., & Blatchford, P. (2011). Effects of class size and adaptive teaching competency on classroom processes and academic outcome....
  • Bryan, T., Burstein, K., & Bryan, J. (2001). Students with learning disabilities: Homework problems and promising practices. Educational...
  • Coley, R. L., Kruzik, C., & Votruba-Drzal, E. (2020). Do family investments explain growing socioeconomic disparities in children’s reading,...
  • Cooper, H., Nye, B., Charlton, K., Lindsay, J., & Greathouse, S. (1996). The effects of summer vacation on achievement test scores: A...
  • Deci, E. L., & Ryan, R. M. (2012). Motivation, personality, and development within embedded social contexts: An overview of self-determination...
  • Ditton, H., & Maaz, K. (2011). Sozioökonomischer Status und soziale Ungleichheit [Socio-economic status and social inequality]. In H....
  • Dochy, F. (1994). Prior knowledge and learning. In T. Husen & T. N. Postlethwaite (Eds.), The International Encyclopedia of Education...
  • Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: What have we learned in 60 years? Frontiers in Psychology, 7, 508....
  • Eccles, J. S., Adler, T. F., Futterman, R., Goff, S. B., Kaczala, C. M., Meece, J. L., & Midgley, C. (1983). Expectancies, values, and...
  • Eccles, J. S., & Wigfield, A. (1995). In the mind of the achiever: The structure of adolescents’ academic achievement related-beliefs...
  • Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153
  • Eickelmann, B., & Drossel, K. (2020). Schule auf Distanz. Perspektiven und Empfehlungen für den neuen Schulalltag. Eine repräsentative...
  • Elliott, L., & Bachman, H. J. (2018). SES disparities in early math abilities: The contributions of parents’ math cognitions, practices...
  • Engzell, P., Frey, A., & Verhagen, M. D. (2021). Learning loss due to school closures during the COVID-19 pandemic. Proceedings of the...
  • Fischer, C., Fischer-Ontrup, C., & Schuster, C. (2020). Individuelle Förderung und selbstreguliertes Lernen. Bedingungen und Optionen...
  • Flunger, B., Mayer, A., & Umbach, N. (2019). Beneficial for some or for everyone? Exploring the effects of an autonomy-supportive intervention...
  • Foster, M. A., Lambert, R., Abbott-Shim, M., McCarty, F., & Franze, S. (2005). A model of home learning environment and social risk factors...
  • Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review...
  • Fredricks, J. A., & McColskey, W. (2012). The measurement of student engagement: A comparative analysis of various methods and student...
  • Froiland, J. M. (2021). A comprehensive model of preschool through high school parent involvement with emphasis on the psychological facets....
  • Froiland, J. M., Davison, M. L., & Worrell, F. C. (2016). Aloha teachers: Teacher autonomy support promotes native Hawaiian and Pacific...
  • Fung, F., Tan, C. Y., & Chen, G. (2018). Student engagement and mathematics achievement: Unraveling main and interactive effects. Psychology...
  • Ganzeboom, H., & Treimann, D. (1996). Internationally comparable measures of occupational status for the 1988 International Standard Classification...
  • Geiser, C. (2011). Data analysis with Mplus. Guilford Press.
  • Gibson, W. A. (1959). Three multivariate models: Factor analysis, latent structure analysis, and latent profile analysis. Psychometrika, 24(3),...
  • Gollwitzer, M. (2012). Latent-class-analysis. In H. Moosbrugger, & A. Kelava (Eds.), Testtheorie und Fragebogenkonstruktion (pp. 295–323)....
  • Gonida, E. N., & Cortina, K. S. (2014). Parental involvement in homework: Relations with parent and student achievement-related motivational...
  • Götz, L., Lingel, K., & Schneider, W. (2013). DEMAT 6+. Deutscher Mathematiktest für sechste Klassen [German mathematics test for...
  • Grätz, M., & Lipps, O. (2021). Large loss in studying time during the closure of schools in Switzerland in 2020. Research in Social Stratification...
  • Gutiérrez, M., Sancho, P., Galiana, L., & Tomás, J. M. (2018). Autonomy support, psychological needs satisfaction, school engagement and...
  • Hannula, M. S., Di Martino, P., Pantziara, M., Zhang, Q., Morselli, F., Heyd-Metzuyanim, E., ... & A Goldin, G. (2016). Attitudes, beliefs,...
  • Heinrich, C. J., Burch, P., Good, A., Acosta, R., Cheng, H., Dillender, M., Kirshbaum, C., Nisar, H., & Stewart, M. (2014). Improving...
  • Helmke, A., & Weinert, F. E. (1997). Bedingungsfaktoren schulischer Leistungen. Max-Planck-Inst. für Psychologische Forschung.
  • Hembree, R. (1990). The nature, effects, and relief of anxiety mathematics. Journal for Research in Mathematics Education, 21(1), 33–46. https://doi.org/10.2307/749455
  • Hernán, M., Hernández-Díaz, S., & Robins, J. (2004). A structural approach to selection bias. Epidemiology, 15(5), 615–625. Retrieved...
  • Hickendorff, M., Edelsbrunner, P. A., Schneider, M., Trezise, K., & McMullen, J. (2017). Informative tools for characterizing individual...
  • Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students’ learning. Second Handbook of Research...
  • Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111–127. https://doi.org/10.1207/s15326985ep4102_4
  • Hofer, S., Nistor, N., & Scheibenzuber, C. (2021). Online teaching and learning in higher education: Lessons learned in crisis situations....
  • Hofer, S. I., Reinhold, F., Loch, F., & Vogel-Heuser, B. (2020). Engineering Students’ Thinking About Technical Systems: An Ontological...
  • Hofer, S. I., & Stern, E. (2016). Underachievement in physics: When intelligent girls fail. Learning and Individual Differences, 51, 119–131.
  • von Hippel, P., & Hamrock, C. (2019). Do test score gaps grow before, during, or between the school years? Measurement artifacts and what...
  • Huber, S. G., & Helm, C. (2020). Lernen in Zeiten der Corona-Pandemie. In D. Fickermann & B. Edelstein (Eds.), „Langsam vermisse ich...
  • Jones, J. I. (2014). An overview of employment and wages in science, technology, engineering, and math (STEM) groups. Beyond the Numbers:...
  • Koch, M., Möller, C., Spinath, F. M. (under review). Are you Swiping, or Just Marking? Development and Evaluation of the Attention Swiping...
  • Köller, O., Fleckenstein, J., Guill, K., & Meyer, J. (2020). Pädagogische und didaktische Anforderungen an die häusliche Aufgabenbearbeitung....
  • Köller, O., Trautwein, U., Luedtke, O., & Baumert, J. (2006). On the interplay of academic achievement, self-concept, and interest in...
  • Kosovich, J. J., Flake, J. K., & Hulleman, C. S. (2017). Short-term motivation trajectories: A parallel process model of expectancy-value....
  • Kuhfeld, M. (2019). Surprising new evidence on summer learning loss. Phi Delta Kappan, 101(1), 25–29. https://doi.org/10.1177/0031721719871560
  • Kuhfeld, M., Soland, J., Tarasawa, B., Johnson, A., Ruzek, E., & Liu, J. (2020). Projecting the potential impact of COVID-19 school closures...
  • Lazarsfeld, P. F., & Henry, N.W. (1968). Latent structure analysis. Houghton Mifflin.
  • Lohr, A., Stadler, M., Schultz-Pernice, F., Chernikova, O., Sailer, M., Fischer, F., & Sailer, M. (2021). On powerpointers, clickerers,...
  • Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for Research...
  • Maguire, E. A., Frith, C. D., & Morris, R. G. M. (1999). The functional neuroanatomy of comprehension and memory: The importance of prior...
  • Marsh, H. W., Lüdtke, O., Trautwein, U., & Morin, A. J. S. (2009). Classical latent profile analysis of academic self-concept dimensions:...
  • Marsh, H. W., & Martin, A. J. (2011). Academic self-concept and academic achievement: Relations and causal ordering. British Journal of...
  • Marsh, H. W., Xu, M., & Martin, A. J. (2012). Self-concept: A synergy of theory, method, and application. In K. R. Harris, S. Graham,...
  • Möller, J., Retelsdorf, J., Köller, O., & Marsh, H. W. (2011). The reciprocal internal/external frame of reference model: An integration...
  • Müller, K., & Ehmke, T. (2013). Soziale Herkunft als Bedingung der Kompetenzentwicklung. In M. Prenzel, C. Sälzer, E. Klieme, & O....
  • Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus User’s Guide (8th ed.). Muthén & Muthén.
  • National Center for Education Statistics (2017). National Assessment of Educational Progress Mathematics. https://www.nationsreportcard.gov/math_2017....
  • Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling:...
  • Oakes, L. M., Kannass, K. N., & Shaddy, D. J. (2002). Developmental changes in endogenous control of attention: The role of target familiarity...
  • OECD. (2016). PISA 2015 results: Excellence and equity in education (Vol. OECD Publishing. https://doi.org/10.1787/9789264266490-en
  • OECD (2019). PISA 2018 results: Combined executive summaries. OECD Publishing.
  • Ortiz, P. A. (2020). Teaching in the time of COVID-19. Biochemistry and Molecular Biology Education, 48(3), 201. https://doi.org/10.1002/bmb.21348
  • Panadero, E., & Alonso Tapia, J. (2014). How do students self-regulate? Review of Zimmerman’s cyclical model of self-regulated learning....
  • Pekrun, R., Vom Hofe, R., Blum, W., Götz, T., Wartha, S., & Jullien, S. (2006). Projekt zur Analyse der Leistungsentwicklung in Mathematik...
  • Prenzel, M., & Drechsel, B. (1996). Ein Jahr kaufmännische Erstausbildung: Veränderungen in Lernmotivation und Interesse [One year of...
  • Quinn, D. M., Cooc, N., McIntyre, J., & Gomez, C. J. (2016). Seasonal dynamics of academic achievement inequality by socioeconomic status...
  • Reinhold, F., Hofer, S. I., Hoch, S., Werner, B., Richter-Gebert, J., & Reiss, K. (2020a). Digital support principles for sustained mathematics...
  • Reinhold, F., Hoch, S., Werner, B., Richter-Gebert, J., & Reiss, K. (2020b). Learning fractions with and without educational technology:...
  • Reinhold, F., Hoch, S., Schiepe-Tiska, A., Strohmaier, A. R., & Reiss, K. (2021). Motivational and Emotional Orientation, Engagement,...
  • Reinhold, F., Reiss, K., Diedrich, J., Hofer, S. I., & Heinze, A., et al. (2019). Mathematische Kompetenz in PISA 2018: Aktueller Stand...
  • Rheinheimer, D. C., Grace-Odeleye, B., Francois, G. E., & Kusorgbor, C. (2010). Tutoring: A support strategy for at-risk students. Learning...
  • Richardson, F. C., & Suinn, R. M. (1972). The mathematics anxiety rating scale: Psychometric data. Journal of Counseling Psychology, 19(6),...
  • Romero, M., & Barberà, E. (2011). Quality of e-learners’ time and learning performance beyond quantitative time-on-task. The International...
  • Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being....
  • Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory,...
  • Ryan, R. M., & Grolnick, W. S. (1986). Origins and pawns in the classroom: Self-report and projective assessments of individual differences...
  • Sälzer, C., Reiss, K., Schiepe-Tiska, A., Prenzel, M., & Heinze, A. (2013). Zwischen Grundlagenwissen und Anwendungsbezug: Mathematische...
  • Schult, J., Mahler, N., Fauth, B., & Lindner, M. A. (2021). Did students learn less during the COVID-19 pandemic? Reading and Mathematics...
  • Schwartz, D. L., Sears, D., & Chang, J. (2007). Reconsidering prior knowledge. Thinking with data, 319–344.
  • Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464.
  • Schweizer, K., & Moosbrugger, H. (2004). Attention and working memory as predictors of intelligence. Intelligence, 32(4), 329–347.
  • Sclove, S. L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 52(3), 333–343.
  • Seidel, T. (2007). The role of student characteristics in studying micro teaching–learning environments. Learning Environments Research, 9(3),...
  • Skinner, E. A., & Belmont, M. J. (1993). Motivation in the classroom: Reciprocal effects of teacher behavior and student engagement across...
  • Skinner, E. A., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational...
  • Smart, R. G. (1966). Subject selection bias in psychological research. Canadian Psychologist/Psychologie canadienne, 7a(2), 115–121. https://doi.org/10.1037/h0083096
  • Soria, K. M., Horgos, B., & McAndrew, M. (2020). Obstacles that may result in delayed degrees for graduate and professional students during...
  • Spearman, J., & Watt, H. M. G. (2013). Perception shapes experience: The influence of actual and perceived classroom environment dimensions...
  • Steinmayr, R., Ziegler, M., & Träuble, B. (2010). Do intelligence and sustained attention interact in predicting academic achievement?...
  • Stern, E. & Hofer, S. I. (2014). Wer gehört aufs Gymnasium? Intelligenzforschung und Schullaufbahnentscheidungen. In Wyss, E. (Ed.). Von...
  • Stone, J. R., III., Alfeld, C., & Pearson, D. (2008). Rigor and relevance: Enhancing high school students’ math skills through career...
  • Stroet, K., Opdenakker, M.-C., & Minnaert, A. (2013). Effects of need supportive teaching on early adolescents’ motivation and engagement:...
  • Tofighi, D., & Enders, C. K. (2007). Identifying the correct number of classes in growth mixture models. In G. R. Hancock & K. M....
  • Valero, P., Graven, M., Jurdak, M., Martin, D., Meaney, T., & Penteado, M. (2015). Socioeconomic influence on mathematical achievement:...
  • Vermunt, J. K., & Magidson, J. (2002). Latent class cluster analysis. In J. Hagenaars & A. McCutcheon (Eds.), Applied latent class...
  • Vroom, V. H. (1964). Work and motivation. Wiley and Sons.
  • Wang, M. T., Fredricks, J. A., Ye, F., Hofkens, T. L., & Linn, J. S. (2016). The math and science engagement scales: Scale development,...
  • Wei, D., Zhang, D., He, J., & Bobis, J. (2019). The impact of perceived teachers’ autonomy support on students’ mathematics achievement:...
  • Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68–81....
  • Wößmann, L., Freundl, V., Grewenig, E., Lergetporer, P., Werner, K., & Zierow, L. (2020). Bildung in der Coronakrise: Wie haben die Schulkinder...
  • Yang, C.-C. (2006). Evaluating latent class analysis models in qualitative phenotype identification. Computational Statistics and Data Analysis,...
  • Yang, C.-C., & Yang, C.-C. (2007). Separating latent classes by information criteria. Journal of Classification, 24(2), 183–203. https://doi.org/10.1007/s00357-007-0010-1
  • Zady, M. F., & Portes, P. R. (2001). When low-SES parents cannot assist their children in solving science problems. Journal of Education...