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Summary All summaries + weblectures for Instructional Design and Evaluation - Educational Science

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This document consist of all the weblectures of the IDE course and the following literature: Web lecture 1: ID&E: Introduction 1.1 Byrnes, J. P. (1992). Categorizing and combining theories of cognitive development and learning. Educational Psychology Review, 4, 309–343. doi:10.1007/BF. 1.2. Hew, K. F., Lan, M., Tang, Y., Jia, C., & Lo, C. K. (2019). Where is the “theory” within the field of educational technology research? British Journal of Educational Technology, 50, 956–971. doi:10.1111/bjet.12770. 1.3 Margaryan, A., Bianco, M., & Littlejohn, A. (2015). Instructional quality of massive open online courses (MOOCs). Computers & Education, 80, 77–83. doi:10.1016/du.2014.08.005. Web lecture 2: Cognitive load: conceptualisation and implications 2.1 Sweller, J., van Merriënboer, J. J. G. & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31, 261–292. doi:10.1007/s. 2.2 de Jong, T. (2010). Cognitive load theory, educational research, and instructional design; some food for thought. Instructional Science, 38, 105–134. doi:10.1007/s. 2.3 Richter, J., Scheiter, K., & Alexander E. (2016). Signaling text-picture relations in multimedia learning: A comprehensive meta-analysis. Educational Research Review, 17,198–36. doi:10.1016/v.2015.12.003. Web lecture 3: Expertise development: conceptualisation and implications 3.1 Ericsson, K. A. (2007). An expert-performance perspective of research on medical expertise: the study of clinical performance. Medical Education, 41(12), 1124–1130. doi:10.1111/j..2007.02946.x. 3.2 Sternberg, R. J. (1999). Intelligence as developing expertise. Contemporary Educational Psychology, 24, 359–375. doi:10.1006/ceps.1998.0998. 3.3 Dunphy, B. C., & Williamson, S. L. (2004). In pursuit of expertise: Toward an educational model for expertise development. Advances in Health Sciences Education, 9, 107–127. doi:10.1023/B:AHSE.6.17220.9c. 11 Web lecture 4: Validity of assessments: conceptualisation and implications 4.1 Kane, M. (2004). Certification testing as an illustration of argument-based validation. Measurement: Interdisciplinary Research & Perspective, 2(3), 135–170. doi:10.1207/smea0203_1. 4.2 Oliveri, M. W., Lawless R. & Mislevy, M. J. (in press). Using evidence-centered design to support the development of culturally and linguistically sensitive collaborative problem-solving assessments. International Journal of Testing. doi:10.1080/.2018.. 4.3 Pellegrino, J. W., DiBello, L. V., & Goldman, S. R. (2016). A framework for conceptualizing and evaluating the validity of instructionally relevant assessments, Educational Psychologist, 51(1), 59–81. doi:10.1080/.2016.. Web lecture 5: Blended learning (learning analytics): conceptualisation and implications 5.1 Bos, N., Groeneveld, C., van Bruggen, J., & Brand-Gruwel, S. (2016). The use of recorded lectures in education and the impact on lecture attendance and exam performance. British Journal of Educational Technology, 47(5), 906–917. doi:10.1111/bjet.12300. 5.2 van Alten, D. C. D., Phielix, C., Janssen, J., Kester, L., (in press). Effects of flipping the classroom on learning outcomes and satisfaction: A meta-Analysis. Educational Research Review. doi:10.1016/v.2019.05.003. 5.3 Wilson, A., Watson, C., Thompson, T. L., Drew, V., & Doyle, S. (2017). Learning analytics: Challenges and limitations. Teaching in Higher Education, 22(8), 991–1007. doi:10.1080/.2017.. Web lecture 6: Game-based learning: conceptualisation and implications 6.1 van Oostendorp, H., Van der Spek, E. D., & Linssen, J. (2014). Adapting the complexity level of a serious game to the proficiency of players. EAI Endorsed Transactions on Serious Games, 1(2), 1–8. doi:10.4108/sg.1.2.e5. 6.2 Shute, V. J., & Kim, Y. J. (2014). Formative and stealth assessment. In Spector, J. M., Merrill, M. D., Elen, J., & Bishop, M. J. (Eds.) Handbook of research on educational communications and technology (pp. 311–321). Springer, New York, NY. 6.3 Wouters, P., van Nimwegen, C., van Oostendorp, H., & van der Spek, E. D. (2013). A meta-analysis of the cognitive and motivational effects of serious games. Journal of Educational Psychology, 105(2), 249–265. doi:10.1037/a. 12 Web lecture 7: Motivation: conceptualisation and implications 7.1 Vansteenkiste, M., Sierens, E., Soenens, B., Luyckx, K., & Lens, W. (2009). Motivational profiles from a self-determination perspective: The quality of motivation matters. Journal of Educational Psychology, 101, 671–688. doi:10.1037/a. 7.2 de Brabander, C. J., & Glastra, F. J. (2018). Testing a unified model of task-specific motivation: How teachers appraise three professional development activities. Frontline Learning Research, 6(1), 54–76. doi:10.14786/flr.v6i1.342. 7.3 Lazowski, R. A., & Hulleman, C. S. (2016). Motivation interventions in education: A Meta-analytic review. Review of Educational Research, 86(2), 602–640. doi:10.3102/

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Voorbeeld van de inhoud

Week 1: ID&E Introduction

Weblecture:

Part 1: Theories

Important in this course: Making choices about educational design, but what might be the
mechanism? Why did you choose this method? Goal master: Making a rational substantiation for the
choice

Course: How to design instruction and evaluation!




Figure: If you’re more active as a learner – you retention will be higher. Side note: The percentages
are not making sense at all! There isn’t any scientific literature which is supporting this figure.
! Be always critical about scientific articles
! Learning pyraMYTH

Part 1: Where is the theory?

How can we apply theory to educational practice?– article Margaryan et al. (2015)

University are trying to organize and setting up MOOCs

Bertolini et al: MOOC’s

,Five principles of Merrill: Theory about ID + five other principles – do they MOOCs meet the design
principles?




Conclusion of the article:
- MOOC are well organized
- Instructional design quality is low!
- Findings seem to be comparable for both types of MOOC’s
- Difficult to transfer theory to educational practice

Notes about the article:
- Do MOOCs have to incorporate all principles? In order to be a good MOOC, you have to
apply to all the principles, but is this really relevant?
- Rational for including principles 6-10? Principles about problem-based learning – can you
apply them to MOOC’s?
- Applied coding scheme? Selective? Dependency?
- Inter-rater reliability?
- Explanation why findings seem to be comparable?

Hew et al. (2019) - Theories (see also Brynes, 1992) – how is theory used when we write scientific
articles?
- Describe, explain and/or predict phenomena
- Offer guidelines: prescriptive and descriptive (how this process occurs)
- Can be refined and generalized to the discipline
- Can be verified/falsified

Conclusion: We don’t use a lot of theories in scientific articles (explicitly) – need for a better use of
theory. Only for correlation research, there is more use of scientific articles

,Discussion:
- Distinction explicit, vague and non?
- Interrater reliability? (overall Kappa)
- Use of % in Table 2
- ‘Educational technology does not appear to be a mature discipline?’

Goal of the course: There are theories about learning, instructional design and assessment and
evaluation + constructive alignment + comparison between theories

Part 2: Theories of learning




If you want to compare learning theories, you can have critic about all theories! You will also see
alignments between the learning theories
- Behaviourism: no insights in the mental processes
- Cognitivism: how do people store information in their head – step by step –
cognition/emotion? – what about whole-tasks?
- Constructivism: whole-task + context taken into account

Connectivism: Learning should arise in the environment – everyone is a node, every node should
connect. You have to combine all this knowledge
- More knowledge available – rapid growth of knowledge
- Knowledge is a shared object, a tool
- Learners are self-directed information brokers

Critic about connectivism:
- How do concepts develop?
- Are learners self-directed information brokers?
- How, when and why are nodes connected?
- How can interaction explain ‘learning’?

So, if every theory has it merits, if we really want to take good comparison: we need MTBS –
Byrnes: Meta-theoretical belief systems (MTBSs): Develop a comparison method to compare
theories

, - Four questions about the beliefs of authors who were in favour of applying a certain kind of
theory:
1. Phenomenon of investigation (do I look at behaviour or cognitive processes)
2. Nature of knowledge:
a. What should be learned? (concepts, procedures, skills)
b. How do mental representations causally affect behaviour? (no, mediate,
yes)
3. Origin of knowledge: learning mechanism (innate or environment)

Importance: Guiding theory development, gaining insight into historical linkages between theories,
determine whether (parts) of theories can be coherently combined

Discussion:
- Shifts in which characteristics / questions are used to define the MTBSs and the groups
o Implicitly applied two sets of criteria
- Groups could have also be defined in another way (e.g. cognitivism and behaviourism?) – why
those three groups?
- Do you advocate theoretical imperialism?
o Theoretical imperialism: one main theory which can educationalist use in instructional
design




Cognition: The mental action or process of acquiring knowledge and understanding through thought,
experiences and senses. It encompasses many aspects of intellectual functions and processes such as
attention, the formation of knowledge, memory and working memory, judgement and evaluation,
reasoning, problem solving, decision making – cognitive processes use existing knowledge and
generate new one


Part 3: Theories of Instructional Design

Learning theories are descriptive: How might learning take place? What factors involve learning? – no
concrete guidelines!

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