A Schema-Based Instructional Design Model for Self-Paced Learning Environments
Abstract
Although research on schema has been widely investigated for the past decades, little research has addressed the development of a systematic instructional design theory using schema principles and processes. This study proposes a systematic schema-based instructional design model, including general and schema analysis, schema-based design, and development processes and techniques for evaluating a learner’s acquired schema. By synthesizing empirical studies, this study comprehensively reviews literature on schema and foundational principles for learning. The goal of the study is to enrich the knowledge base of schema-based instructional design for different learning environments. Thus, the study is concluded by a discussion on how to utilize a schema-based instructional design for self-paced learning environments with additional implications and further recommendations.
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Cites
Cognitive load theory, learning difficulty, and instructional design
Sweller, J. (1994) · Learning and Instruction · doi:10.1016/0959-4752(94)90003-5 · Cited by 3,801 · see citing works
Cognitive Load Theory and the Format of Instruction
Chandler, P., & Sweller, J. (1991) · Cognition and Instruction · doi:10.1207/s1532690xci0804_2 · Cited by 2,894 · see citing works
Cognitive Architecture and Instructional Design: 20 Years Later
Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019) · Educational Psychology Review · doi:10.1007/s10648-019-09465-5 · Cited by 2,337 · cited 1× · see citing works
“The major strengths of subjective techniques are their simplicity and applicability; however, the simplicity can also be seen as a weakness, because results may provide a general rather than specific measure of cognitive load [60] (Sweller et al., 2019).”
BackgroundCognitive load theory, educational research, and instructional design: some food for thought
de Jong, T. (2010) · Instructional Science · doi:10.1007/s11251-009-9110-0 · Cited by 1,180 · cited 3× · see citing works
“…trackers, neuro-imaging techniques, and heart rate monitors equipped in mobile devices (e.g., smart watches) combined with the affordability of such technologies, have made it possible to collect students’ physiological data more easily than ever before in self-paced online learning contexts [72].”
BackgroundMethodInfluentialCognitive load theory and educational technology
Sweller, J. (2020) · Educational Technology Research and Development · doi:10.1007/s11423-019-09701-3 · Cited by 911 · see citing works
Karbach, J., & Kray, J. (2009) · Developmental Science · doi:10.1111/j.1467-7687.2009.00846.x · Cited by 694 · see citing works
Working Memory, Long-term Memory, and Instructional Design
Sweller, J. (2016) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2015.12.002 · Cited by 192 · see citing works
Measuring cognitive load during procedural skills training with colonoscopy as an exemplar
Sewell, J. L., Boscardin, C. K., Young, J. Q., ten Cate, O., & O'Sullivan, P. S. (2016) · Medical Education · doi:10.1111/medu.12965 · Cited by 64 · see citing works
Darejeh, A., Marcus, N., & Sweller, J. (2021) · Educational Technology Research and Development · doi:10.1007/s11423-021-10024-5 · Cited by 29 · cited 1× · see citing works
“As learners link new knowledge to existing knowledge, learning outcomes can be increased while also decreasing cognitive load [46].”
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Flagged first, then by citations
- Authors
- Jung, E., Lim, R., & Kim, D.
- Venue
- Education Sciences
- Publisher
- MDPI AG
- Published
- 2022-04-12
- Volume
- 12
- Issue
- 4
- Pages
- 271
- ISSN
- 2227-7102
- Cited by
- 32
- References
- 9
- Language
- en
- Funders
- National Research Foundation of Korea (NRF-2021S1A5A8063131)
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