Title |
How to build better memory training games
|
---|---|
Published in |
Frontiers in Systems Neuroscience, January 2015
|
DOI | 10.3389/fnsys.2014.00243 |
Pubmed ID | |
Authors |
Jenni Deveau, Susanne M. Jaeggi, Victor Zordan, Calvin Phung, Aaron R. Seitz |
Abstract |
Can we create engaging training programs that improve working memory (WM) skills? While there are numerous procedures that attempt to do so, there is a great deal of controversy regarding their efficacy. Nonetheless, recent meta-analytic evidence shows consistent improvements across studies on lab-based tasks generalizing beyond the specific training effects (Au et al., 2014; Karbach and Verhaeghen, 2014), however, there is little research into how WM training aids participants in their daily life. Here we propose that incorporating design principles from the fields of Perceptual Learning (PL) and Computer Science might augment the efficacy of WM training, and ultimately lead to greater learning and transfer. In particular, the field of PL has identified numerous mechanisms (including attention, reinforcement, multisensory facilitation and multi-stimulus training) that promote brain plasticity. Also, computer science has made great progress in the scientific approach to game design that can be used to create engaging environments for learning. We suggest that approaches integrating knowledge across these fields may lead to a more effective WM interventions and better reflect real world conditions. |
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United Kingdom | 3 | 20% |
Italy | 1 | 7% |
France | 1 | 7% |
Norway | 1 | 7% |
Ireland | 1 | 7% |
Unknown | 3 | 20% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 12 | 80% |
Scientists | 2 | 13% |
Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
Geographical breakdown
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United States | 2 | 1% |
Switzerland | 1 | <1% |
Spain | 1 | <1% |
Germany | 1 | <1% |
Unknown | 186 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 45 | 23% |
Student > Master | 27 | 14% |
Researcher | 25 | 13% |
Student > Bachelor | 18 | 9% |
Student > Doctoral Student | 12 | 6% |
Other | 38 | 20% |
Unknown | 28 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 82 | 42% |
Neuroscience | 17 | 9% |
Computer Science | 11 | 6% |
Social Sciences | 10 | 5% |
Medicine and Dentistry | 9 | 5% |
Other | 30 | 16% |
Unknown | 34 | 18% |