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What Can We Learn from Theoretical Considerations and Empirical Evidence on Learning in Higher Education? Implications for an Interdisciplinary Research Framework

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Abstract

Since the development of the hypertext markup language (HTML), a myriad of data from different sources has become increasingly cross-linked, resulting in entire information landscapes; more than 21 billion electronic devices (Web 4.0) will be in use by 2020. Access to and processing of multimedia content and unverified and algorithmically preselected information are constitutive elements of learning in the Internet Age. As learning occurs in- and outside of formal higher education institutions and cannot be explained by educational or technological factors alone, it is a crucial cross-disciplinary topic, equally important for all areas of science and education. Yet, research on learning in higher education has not kept up with the rapid technological and social developments in recent years, and little is known about learning in agile (cooperative) online environments. This paper contributes to reviewing and consolidating the state of research on learning in higher education using the Internet. Considering theoretical fundamentals and empirical evidence, we argue for developing a new interdisciplinary research framework that goes beyond cognitive, affective, technological, information-literal, or moral facets, that integrates complementary, cross-disciplinary perspectives, and that lays foundations for the analysis of learning in higher education in the twenty-first century.

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Notes

  1. 1.

    We would like to thank Howard Gardner for calling out awareness to this aspect.

References

  • Alexander, P. A. (1997). Mapping the multidimensional nature of domain learning: The interplay of cognitive, motivational, and strategic forces. In M. L. Maehr & P. R. Pintrich (Eds.), Advances in motivation and achievement (Vol. 10, pp. 213–250). Greenwich, CT: JAI.

    Google Scholar 

  • Alexander, P., & List, A. (2017). Analyzing and integrating models of multiple text comprehension. Educational Psychologist, 52(3), 143–147. https://doi.org/10.1080/00461520.2017.1328309

    Article  Google Scholar 

  • Alexander, P., Murphy, K., & Sun, Y. (2018). Knowledge and belief change in academic development. In H. Fives & D. Dinsmore (Eds.), The model of domain learning. Understanding the development of expertise. New York: Routledge Taylor & Francis.

    Google Scholar 

  • Allalouf, A. (2019). Thirty years of research on the sources of DIF in translated tests. Presentation at the NCME, Toronto, 4–8 April.

    Google Scholar 

  • Arbeitsgruppe Curriculum 4.0. (2018). Curriculumentwicklung und Kompetenzen für das digitale Zeitalter – Thesen und Empfehlungen der AG Curriculum 4.0 des Hochschulforum Digitalisierung (Arbeitspapier: Vol. 39). Berlin: Hochschulforum Digitalisierung.

    Google Scholar 

  • Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3(3), 265–299.

    Article  Google Scholar 

  • Behrens, J. T., Mislevy, R. J., DiCerbo, K. E., & Levy, R. (2010). An evidence center design for learning and assessment in the digital world. CRESST Report 778. Los Angeles: UCLA-National center for Research on Evaluation, Standards, and Student Testing. Retrieved August 25, 2016, from http://files.eric.ed.gov/fulltext/ED520431.pdf

    Google Scholar 

  • Bernstein, D. M., Erdfelder, E., Meltzoff, A. N., Peria, W., & Loftus, G. R. (2011). Hindsight bias from 3 to 95 years of age. Journal of Experimental Psychology, Learning, Memory, and Cognition, 37(2), 378–391.

    Article  Google Scholar 

  • Bronfenbrenner, U. (1977). Toward an experimental ecology of human development. American Psychologist, 32(7), 513–531. https://doi.org/10.1037/0003-066X.32.7.513

    Article  Google Scholar 

  • Bronfenbrenner, U. (1995). Ecological models of human development. In T. Husén (Ed.), The international encyclopedia of education (2nd ed., pp. 1643–1647). Oxford: Pergamon.

    Google Scholar 

  • Brooks, D. C. (2016). ECAR Study of Undergraduate Students and Information Technology. Louisville. Retrieved from https://library.educause.edu/~/media/files/library/2016/10/ers1605.pdf

  • Brückner, S. (2017). Prozessbezogene Validierung anhand von mentalen Operationen bei der Bearbeitung wirtschaftswissenschaftlicher Testaufgaben. Landau: Empirische Pädagogik.

    Google Scholar 

  • Brückner, S., & Zlatkin-Troitschanskaia, O. (2018). Threshold concepts for modeling and assessing higher education students’ understanding and learning in economics. In O. Zlatkin-Troitschanskaia, M. Toepper, H. A. Pant, C. Lautenbach, & C. Kuhn (Eds.), Assessment of learning outcomes in Higher Education: Cross-National comparisons and perspectives (pp. 103–121). Basel: Springer International.

    Chapter  Google Scholar 

  • Brückner, S., Förster, M., Zlatkin-Troitschanskaia, O., Happ, R., Walstad, W. B., Yamaoka, M., et al. (2015). Gender effects in assessment of economic knowledge and understanding: Differences among Undergraduate Business and Economics Students in Germany, Japan, and the United States. Peabody Journal of Education, 90(4), 503–518.

    Article  Google Scholar 

  • Bruner, J. S. (1966). Toward a theory of instruction. New York: W.W. Norton.

    Google Scholar 

  • Cadwalladr, C. (2018, March 18). ‘I made Steve Bannon’s psychological warfare tool’: meet the data war whistleblower. The Guardian. Retrieved from https://www.theguardian.com/news/2018/mar/17/data-war-whistleblower-christopher-wylie-faceook-nix-bannon-trump

  • Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054–1064.

    Article  Google Scholar 

  • Ciampaglia, G. (2018). The digital misinformation pipeline. In O. Zlatkin-Troitschanskaia, G. Wittum, & A. Dengel (Eds.), Positive learning in the age of information (pp. 413–422). Wiesbaden: Springer.

    Google Scholar 

  • Dabbagh, N., & Kitsantas, A. (2012). Personal learning environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. The Internet and Higher Education, 15(1), 3–8.

    Article  Google Scholar 

  • Demetriadis, S. (2004). Interaction between learner’s internal and external representation in multimedia environment: A state-of-the-art. Research report of the Kaleidoscope Network of Excellence (IST 507838), Deliverable 21.1.1. State-of-the-art report, Kaleidoscope Network of Excellence.

    Google Scholar 

  • Dewey, J. (1997). Experience and education. The Kappa Delta Pi Lecture Series. New York: Simon & Schuster.

    Google Scholar 

  • Elkasrawi, S., Abdelsamad, A., Bukhari, S. S., & Dengel, A. (2016). What you see is what you get? Automatic image verification for online news content. In: DAS IAPR International Workshop on Document Analysis Systems (DAS-2016), 12th IAPR International Workshop on Document Analysis Systems, located at DAS, April 11–14, Santorini, Greece, IEEE-Xplore digital library.

    Google Scholar 

  • Ericsson, K. A. (2008). Deliberate practice and acquisition of expert performance: A general overview. Academic Emergency Medicine, 15(11), 988–994. https://doi.org/10.1111/j.1553-2712.2008.00227.x

    Article  Google Scholar 

  • Feierabend, S., Plankenhorn, T., & Rathgeb, T. (2017). JIM 2017 Jugend, Information, (Multi-)Media: Basisstudie zum Medienumgang 12- bis 19-Jähriger in Deutschland. Stuttgart.

    Google Scholar 

  • Förster, M., Brückner, S., & Zlatkin-Troitschanskaia, O. (2015). Assessing the financial knowledge of university students in Germany. Empirical Research in Vocational Education and Training, 7(6), 1–20. https://doi.org/10.1186/s40461-015-0017-5

    Article  Google Scholar 

  • Fossland, T. (2015). Moving beyond learning in net-based higher education? In Academic bildung in net-based higher education: Moving beyond learning (pp. 19–30). Abingdon: Routledge.

    Chapter  Google Scholar 

  • Gadiraju, U., Yu, R., Dietze, S., & Holtz, P. (2018). Analyzing knowledge gain of users in informational search sessions on the web. In C. Shah, N. J. Belkin, K. Byström, J. Huang, & F. Scholer (Eds.), CHIIR’18: Proceedings of the 2018 Conference on Human Information Interaction & Retrieval: March 11-15, 2018, New Brunswick, NJ, USA (pp. 2–11). New York, NY: The Association for Computing Machinery. https://doi.org/10.1145/3176349.3176381

    Chapter  Google Scholar 

  • Gagné, R. M. (1985). The conditions of learning and theory of instruction. New York: CBS College Publishing.

    Google Scholar 

  • Gardner, H. (1999). Intelligence reframed: Multiple intelligences for the 21st century. New York: Basic Books.

    Google Scholar 

  • Gardner, H. (2011). Frames of mind: The theory of multiple intelligences. New York: Basic Books.

    Google Scholar 

  • Gardner, H. (2018). Higher education: A Platonic ideal. In O. Zlatkin-Troitschanskaia, G. Wittum, & A. Dengel (Eds.), Positive learning in the age of information (pp. 7–22). Wiesbaden: Springer.

    Google Scholar 

  • Gigerenzer, G. (2015). Simply rational: Decision making in the real world. Oxford series in evolution and cognition. New York: Oxford University Press.

    Book  Google Scholar 

  • Gigerenzer, G., & Todd, P. M. (2001). Simple heuristics that make us smart: Evolution and cognition. Oxford: Oxford University Press.

    Google Scholar 

  • Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. The Internet and Higher Education, 19, 18–26.

    Article  Google Scholar 

  • Goldman, S. R., Britt, M. A., Brown, W., Cribb, G., George, M., Greenleaf, C., et al. (2016). Disciplinary literacies and learning to read for understanding: A conceptual framework for disciplinary literacy. Educational Psychologist, 51(2), 219–246. https://doi.org/10.1080/00461520.2016.1168741

    Article  Google Scholar 

  • Hahnel, C., Kröhne, U., Goldhammer, F., Schoor, C., Mahlow, N., & Artelt, C. (2019a). Validating process variables of sourcing in an assessment of multiple document comprehension. British Journal of Educational Psychology. https://doi.org/10.1111/bjep.12278

  • Hahnel, C., Schoor, C., Kröhne, U., Goldhammer, F., Mahlow, N., & Artelt, C. (2019b). The role of cognitive load for university students’ comprehension of multiple documents. Zeitschrift für Pädagogische Psychologie, 33, 105–118. https://doi.org/10.1024/1010-0652/a000238.

    Article  Google Scholar 

  • Happ, R., & Zlatkin-Troitschanskaia, O. (2014). Assessing the quality of the Bachelor Degree Courses: An analysis of their effects’ on students acquisition of economic content knowledge. Zeitschrift für Hochschulentwicklung, 9(2), 64–77.

    Article  Google Scholar 

  • Happ, R., Zlatkin-Troitschanskaia, O., & Schmidt, S. (2016). An analysis of economic learning among undergraduates in introductory economics courses in Germany. The Journal of Economic Education, 47(4), 300–310. https://doi.org/10.1080/00220485.2016.1213686

    Article  Google Scholar 

  • Hocevar, K. P., Flanagin, A. J., & Metzger, M. J. (2014). Social media self-efficacy and information evaluation online. Computers in Human Behavior, 39, 254–262. https://doi.org/10.1016/j.chb.2014.07.020

    Article  Google Scholar 

  • Jitomirski, J., Zlatkin-Troitschanskaia, O., Schlax, J., Kühling-Thees, C., Happ, R., Schipolowski, S., et al. (2019). The relation between general intellectual ability and study-related media use among University Students in Economics. Paper presented at the American Education Research Association (AERA) Annual Meeting 2019 in Toronto, Canada.

    Google Scholar 

  • Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.

    Google Scholar 

  • Kammerer, Y., & Gerjets, P. (2012). Effects of search interface and Internet-specific epistemic beliefs on source evaluations during Web search for medical information: An eye-tracking study. Behaviour & Information Technology, 31(1), 83–97. https://doi.org/10.1080/0144929X.2011.599040

    Article  Google Scholar 

  • Klein, P., Küchemann, S., Brückner, S., Zlatkin-Troitschanskaia, O., & Kuhn, J. (2019). Student understanding of graph slope and area under a curve: A replication study comparing first year physics and economic students. Physical Review of Physics Education Research, 14, 020109.

    Google Scholar 

  • Köhler, W. (1972). The task of Gestalt psychology. Princeton: Princeton University Press.

    Google Scholar 

  • Kuhn, D. (1999). A developmental model of critical thinking. Educational Researcher, 28(2), 16–46. https://doi.org/10.3102/0013189X028002016

    Article  Google Scholar 

  • Land, R. (2016). TOIL AND TROUBLE: Threshold concepts as a pedagogy of uncertainty. In R. Land, J. H. F. Meyer, & M. T. Flanagan (Eds.), Threshold concepts in practice (pp. 11–24). Rotterdam: Sense.

    Chapter  Google Scholar 

  • Lazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., et al. (2018). The science of fake news. Science, 359(6380), 1094–1096. https://doi.org/10.1126/science.aao2998

    Article  Google Scholar 

  • Luhmann, N. (2012). Introduction to systems theory. Cambridge: Polity.

    Google Scholar 

  • Lynch, M. P. (2016). Googling is believing: Trumping the informed citizen. New York Times. Retrieved from http://opinionator.blogs.nytimes.com/2016/03/09/googling-is-believingtrumping-the-informed-citizen/

  • Marton, F., & Svensson, L. (1979). Conceptions of research in student learning. Higher Education, 8(4), 471–486. https://doi.org/10.1007/BF01680537

    Article  Google Scholar 

  • Mayer, R. E. (2005). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning. New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Mehler, A., Zlatkin-Troitschanskaia, O., Hemati, W., Molerov, D., Lücking, A., & Schmidt, S. (2018). Integrating computational linguistic analysis of multilingual learning data and educational measurement approaches to explore learning in higher education. In O. Zlatkin-Troitschanskaia, G. Wittum, & A. Dengel (Eds.), Positive learning in the age of information (pp. 145–196). Wiesbaden: Springer.

    Google Scholar 

  • Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational measurement (3rd ed., pp. 13–103). New York: Macmillan.

    Google Scholar 

  • Meyer, J., Land, R., & Baillie, C. (2010). Threshold concepts and transformational learning. Educational futures: rethinking theory and practice. Rotterdam: Sense.

    Google Scholar 

  • Mislevy, R. J. (1996). Test theory reconceived. Journal of Educational Measurement, 33(4), 379–416. https://doi.org/10.1111/j.1745-3984.1996.tb00498.x

    Article  Google Scholar 

  • Mislevy, R. J., & Haertel, G. D. (2006). Implications of evidence centered design for educational testing. Educational Measurement: Issues and Practice, 25(4), 6–20.

    Article  Google Scholar 

  • Mushtaq, A. J., & Benraghda, A. (2018). The effects of social media on the Undergraduate Students’ Academic Performance. Library Philosophy and Practice.

    Google Scholar 

  • Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Newman, F., & Scurry, J. E. (2015). Higher education and the digital Rapids. International Higher Education, (26). https://doi.org/10.6017/ihe.2002.26.6968

  • Oeberst, A., de Vreeze, J., & Cress, U. (2018). The norm of neutrality in collaborative knowledge construction. In O. Zlatkin-Troitschanskaia, G. Wittum, & A. Dengel (Eds.), Positive learning in the age of information (pp. 209–220). Wiesbaden: Springer.

    Google Scholar 

  • Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. https://doi.org/10.1207/S15326985EP3801_1

    Article  Google Scholar 

  • Pellegrino, J. W., & Hilton, M. L. (2012). Education for life and work: Developing transferable knowledge and skills in the 21st century. Washington, D.C.: National Academies Press. https://doi.org/10.17226/13398

    Book  Google Scholar 

  • Persike, M., & Friedrich, J. D. (2016). LERNEN MIT DIGITALEN MEDIEN AUS STUDIERENDENPERSPEKTIVE: Sonderauswertung aus dem CHE Hochschulranking für die deutschen Hochschulen. Arbeitspapier: [LERNING WITH DIGITAL MEDIA FROM A STUDENT PERSPECTIVE: Special analysis of the CHE higher education institution tanking for German HEIs. Working paper:] 17. Berlin: Hochschulforum Digitalisierung.

    Google Scholar 

  • Piaget, J. (1972). The psychology of the child. New York: Basic Books.

    Google Scholar 

  • Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211–227.

    Article  Google Scholar 

  • Schmidt, S., Zlatkin-Troitschanskaia, O., & Fox, J.-P. (2016). Pretest-Posttest-Posttest multilevel IRT modeling of competence growth of students in Higher Education in Germany. Journal of Educational Measurement, 53(3), 332–351. https://doi.org/10.1111/jedm.12115

    Article  Google Scholar 

  • Shavelson, R. J., Zlatkin-Troitschanskaia, O., & Mariño, J. P. (2018). International performance assessment of learning in higher education (iPAL): Research and development. In O. Zlatkin-Troitschanskaia, M. Toepper, H. A. Pant, C. Lautenbach, & C. Kuhn (Eds.), Assessment of learning outcomes in higher education: Cross-national comparisons and perspectives (Vol. 66, pp. 193–214). Cham: Springer. https://doi.org/10.1007/978-3-319-74338-7_10

    Chapter  Google Scholar 

  • Shavelson, R. J., Zlatkin-Troitschanskaia, O., Beck, K., Schmidt, S., & Marino, J. P. (2019). Assessment of University Students’ critical thinking: Next generation performance assessment. International Journal of Testing, 37(9), 1–20.

    Google Scholar 

  • Shrivastav, H., & Hiltz, S. R. (2013). Information overload in technology-based education: A meta-analysis. Americas Conference on Information Systems, Chicago, Illinois.

    Google Scholar 

  • Simon, H. A. (1959). Theories of decision-making in economics and behavioral science. The American Economic Review, 49(3), 253–283.

    Google Scholar 

  • Skinner, B. F. (1953). Science and human behavior. New York: Free Press.

    Google Scholar 

  • Snow, R. E. (1989). Cognitive-conative aptitude interactions in learning. In R. Kanfer, P. I. Ackermann, & R. Cudeck (Eds.), Abilities, motivation, and methodology (pp. 435–474). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Somerville, M. M., Smith, G. W., & Smith Macklin, A. (2008). The ETS iSkills TM Assessment: A digital age tool. The Electronic Library, 26(2), 158–171.

    Article  Google Scholar 

  • Stanovich, K. E. (2011). Rationality and the reflective mind. New York: Oxford University Press.

    Google Scholar 

  • Steffens, Y., Schmitt, I. L., & Aßmann, S. (2017). Mediennutzung Studierender: Über den Umgang mit Medien in hochschulischen Kontexten. Systematisches Review nationaler und internationaler Studien zur Mediennutzung Studierender. https://doi.org/10.13154/rub.106.95

  • Subrahmanyam, K., Michikyan, M., Clemmons, C., Carrillo, R., Uhls, Y. T., & Greenfield, P. M. (2014). Learning from paper, learning from screens: Impact of screen reading and multitasking conditions on reading and writing among college student. International Journal of Cyber Behavior, Psychology and Learning, 3(4), 1–27.

    Article  Google Scholar 

  • Thaler, R. (2009). Nudge. Improving decisions about health, wealth and happiness. London: Penguin.

    Google Scholar 

  • Van Lehn, K., & van de Sande, B. (2009). Acquiring conceptual expertise from modeling: The case of elementary physics. In K. A. Ericsson (Ed.), Development of professional expertise (pp. 356–378). New York: Cambridge University Press.

    Google Scholar 

  • Vergès, P., & Ryba, R. (2012). Social representations of the economy. In A. S. De Rosa (Ed.), Cultural dynamics of social representation. Social representations in the “Social Arena” (1st ed., pp. 233–245). London: Routledge.

    Google Scholar 

  • Verkade, H., Mulhern, T. D., Lodge, J. M., Elliott, K., Cropper, S., Rubinstein, B., et al. (2017). Misconceptions as a trigger for enhancing student learning in higher education: A handbook for educators. Melbourne: The University of Melbourne.

    Google Scholar 

  • Von der Mühlen, S., Richter, T., Schmid, S., Berthold, K., & Schmidt, L. M. (2015). Use of source-related strategies in evaluating multiple psychology texts: A student-scientist comparison. Reading and Writing (online first). https://doi.org/10.1007/s11145-015-9601-0

    Article  Google Scholar 

  • Von der Mühlen, S., Richter, T., Schmid, S., Schmidt, L. M., & Berthold, K. (2016). Judging the plausibility of arguments in scientific texts: A student-scientist comparison. Thinking & Reasoning, 22, 221–246.

    Article  Google Scholar 

  • Walstad, W. B., & Wagner, J. (2016). The disaggregation of value-added test scores to assess learning outcomes in economics courses. The Journal of Economic Education, 47(2), 121–131.

    Article  Google Scholar 

  • Weinert, F. E. (2001). Concept of competence: A conceptual clarification. In D. S. Rychen & L. H. Salganik (Eds.), Defining and selecting key competencies (pp. 45–65). Ashland: Hogrefe & Huber.

    Google Scholar 

  • Wilson, J. P., Hugenberg, K. J., & Bernstein, M. J. (2013). The Cross-Race effect and eyewitness identification: How to improve recognition and reduce decision errors in eyewitness situations. Social Interest and Policy Review, 7, 83–113.

    Article  Google Scholar 

  • Wineburg, S., & McGrew, S. (2016). Why students can’t Google their way to truth. Education Week. Retrieved from http://www.edweek.org/ew/articles/2016/11/02/why-studentscant-google-their-way-to.html

  • Wineburg, S., Breakstone, J., McGrew, S., & Ortega, T. (2018). Why Google Can’t Save Us: The challenges of our post-Gutenberg moment. In O. Zlatkin-Troitschanskaia, G. Wittum, & A. Dengel (Eds.), Positive learning in the age of information (pp. 221–228). Wiesbaden: Springer.

    Google Scholar 

  • Zlatkin-Troitschanskaia, O., Happ, R., Förster, M., Preuße, D., Schmidt, S., & Kuhn, C. (2013). Analyse der Ausprägung und Entwicklung der Fachkompetenzvon Studierenden der Wirtschaftswissenschaften und Wirtschaftspädagogik. In O. Zlatkin-Troitschanskaia, R. Nickolaus, & K. Beck (Hrsg.), Kompetenzmodellierung und Kompetenzmessung bei Studierenden der Wirtschaftswissenschaften und der Ingenieurwissenschaften [Sonderheft]. Lehrerbildung auf dem Prüfstand, 6(1), 69–92.

    Google Scholar 

  • Zlatkin-Troitschanskaia, O., Förster, M., Brückner, S., & Happ, R. (2014). Insights from the German assessment of business and economics competence. In H. Coates (Ed.), Assessing learning outcomes: Perspectives for quality improvement (pp. 175–197). Frankfurt am Main: Lang.

    Google Scholar 

  • Zlatkin-Troitschanskaia, O., Shavelson, R. J., & Kuhn, C. (2015). The international state of research on measurement of competency in higher education. Studies in Higher Education, 40(3), 393–411. https://doi.org/10.1080/03075079.2015.1004241

    Article  Google Scholar 

  • Zlatkin-Troitschanskaia, O., Schmidt, S., Brückner, S., Förster, M., Yamaoka, M., & Asano, T. (2016). Macroeconomic knowledge of higher education students in Germany and Japan - A multilevel analysis of contextual and personal effects. Assessment & Evaluation in Higher Education, 41(5), 787–801. https://doi.org/10.1080/02602938.2016.1162279

    Article  Google Scholar 

  • Zlatkin-Troitschanskaia, O., Schmidt, S., Molerov, D., Shavelson, R. J., & Berliner, D. (2018). Conceptual fundamentals for a theoretical and empirical framework of positive learning. In O. Zlatkin-Troitschanskaia, G. Wittum, & A. Dengel (Eds.), Positive learning in the age of information (pp. 29–50). Wiesbaden: Springer. https://doi.org/10.1007/978-3-658-19567-0

    Chapter  Google Scholar 

  • Zlatkin-Troitschanskaia, O., Kuhn, C., Brückner, S., & Leighton, J. P. (2019a). Evaluating a technology-based assessment (TBA) to measure teachers’ action-related and reflective skills. International Journal of Testing., 19(2), 148–171.

    Article  Google Scholar 

  • Zlatkin-Troitschanskaia, O., Shavelson, R. J., Schmidt, S., & Beck, K. (2019b). On the complementarity of holistic and analytic approaches to performance assessment scoring. The British Journal of Educational Psychology. https://doi.org/10.1111/bjep.12286

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Acknowledgements.

We thank all PLATO colleagues and researchers for their valuable input to this contribution, in particular, Patricia Alexander, Michael Posner, Richard Shavelson, and William Walstad.

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  1. Johannes Gutenberg University Mainz, Mainz, Germany

    Olga Zlatkin-Troitschanskaia, Sebastian Brückner & Walter Bisang

  2. Humboldt University of Berlin, Berlin, Germany

    Dimitri Molerov

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Correspondence to Olga Zlatkin-Troitschanskaia .

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  1. Department of Business and Economics Education, Johannes Gutenberg University Mainz, Mainz, Germany

    Olga Zlatkin-Troitschanskaia

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Zlatkin-Troitschanskaia, O., Brückner, S., Molerov, D., Bisang, W. (2019). What Can We Learn from Theoretical Considerations and Empirical Evidence on Learning in Higher Education? Implications for an Interdisciplinary Research Framework. In: Zlatkin-Troitschanskaia, O. (eds) Frontiers and Advances in Positive Learning in the Age of InformaTiOn (PLATO). Springer, Cham. https://doi.org/10.1007/978-3-030-26578-6_21

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  • DOI: https://doi.org/10.1007/978-3-030-26578-6_21

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