mGBL's main benefit is affective, which may sacrifice effectiveness or efficiency to increase motivation and engagement¶

Claim · All claims
Evidence · 1 study (2 entries) · theoretical r2 · q1
Currency · newest study 2021 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? Giannakas et al. (2018) indicate the main benefit of mGBL is affective, reflecting the appeal outcome associated with values about priorities. → Honebein Peter C 2021 q1 i? If the main benefit is affective, mGBL may be sacrificing effectiveness (mastery of instructional objectives) or efficiency (cost, time, and resources) to increase motivation and engagement. → Honebein Peter C 2021 (2)

Evidence¶

Honebein Peter C 2021¶

Honebein Peter C. (2021). How should theory guide a ‘shift to digital’ in mobile game-based learning? Educational Technology Research and Development. https://doi.org/10.1007/s11423-020-09929-4

q1 · i? · theoretical · r2

Theoretical commentary interpreting a specific page of the Giannakas et al. (2018) review to identify the affective benefit of mGBL. The article offers no empirical data for this claim.

"You can see this play out in Giannakas et al. (2018) when, on p. 363, the authors indicate the main benefit of mGBL is affective, which reflects the “appeal” outcome associated with values about priorities."

Honebein Peter C 2021 (2)¶

Honebein Peter C. (2021). How should theory guide a ‘shift to digital’ in mobile game-based learning? Educational Technology Research and Development. https://doi.org/10.1007/s11423-020-09929-4

q1 · i? · theoretical · r2

Theoretical commentary inferring a potential trade-off between affective appeal and effectiveness or efficiency in mGBL design. The article offers no empirical data for this claim.

"If this is the case, then mGBL may be sacrificing effectiveness (mastery of instructional objectives) or efficiency (cost, time, and resources) to increase motivation and engagement."

Discussion¶

Related Claims¶

• The six dimensions of the Giannakas et al. (2018) review are categories of conditions, and the review lacks guidance for analyzing values — related
• Giannakas et al. (2018) mixes instructional methods with learning theories, listing problem solving, experiential learning, situated learning, and task-based language learning as learning theories — related
• mGBL makes more sense for teaching lower-level enabling content than complex performances that mix multiple learning domains — related
• The Giannakas et al. (2018) review found that transitioning game-based learning to mobile requires well-designed technological and pedagogical solutions, not quick modification — related