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Growth Mindset Predicts Student Achievement and Behavior in Mobile Learning

Published: 24 June 2019 Publication History

Abstract

Students' personal qualities other than cognitive ability are known to influence persistence and achievement in formal learning environments, but the extent of their influence in digital learning environments is unclear. This research investigates non-cognitive factors in mobile learning in a resource-poor context. We surveyed 1,000 Kenyan high school students who use a popular SMS-based learning platform that provides formative assessments aligned with the national curriculum. Combining survey responses with platform interaction logs, we find growth mindset to be one of the strongest predictors of assessment scores. We investigate theory-based behavioral mechanisms to explain this relationship. Although students who hold a growth mindset are not more likely to persist after facing adversity, they spend more time on each assessment, increasing their likelihood of answering correctly. Results suggest that cultivating a growth mindset can motivate students in a resource-poor context to excel in a mobile learning environment.

References

[1]
Nicholas O Alozie and Patience Akpan-Obong. 2017. The Digital Gender Divide: Confronting Obstacles to Women's Development in Africa. Development Policy Review 35, 2 (2017), 137--160.
[2]
Susan A Ambrose, Michael W Bridges, Michele DiPietro, Marsha C Lovett, and Marie K Norman. 2010. How learning works: Seven research-based principles for smart teaching. John Wiley & Sons.
[3]
John R Anderson, Albert T Corbett, Kenneth R Koedinger, and Ray Pelletier. 1995. Cognitive tutors: Lessons learned. The journal of the learning sciences 4, 2 (1995), 167--207.
[4]
John W Atkinson. 1957. Motivational determinants of risk-taking behavior. Psychological review 64, 6p1 (1957), 359.
[5]
Albert Bandura. 1977. Self-efficacy: toward a unifying theory of behavioral change. Psychological review 84, 2 (1977), 191.
[6]
Albert Bandura. 1986. The explanatory and predictive scope of self-efficacy theory. Journal of social and clinical psychology 4, 3 (1986), 359--373.
[7]
Lisa S Blackwell, Kali H Trzesniewski, and Carol S Dweck. 2007. Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child development 78, 1 (2007), 246--263.
[8]
Tom H Brown. 2005. Towards a model for m-learning in Africa. International Journal on E-learning 4, 3 (2005), 299--315.
[9]
Tom H Brown and Lydia S Mbati. 2015. Mobile learning: Moving past the myths and embracing the opportunities. the international review of research in open and distributed learning 16, 2 (2015).
[10]
S van Buuren and Karin Groothuis-Oudshoorn. 2010. mice: Multivariate imputation by chained equations in R. Journal of statistical software (2010), 1--68.
[11]
CIO East Africa. 2018. Shupavu 291 nominated for GLOMO Awards 2018. https://www.cio.co.ke/shupavu-291-nominated-glomo-awards-2018/
[12]
Susana Claro, David Paunesku, and Carol S Dweck. 2016. Growth mindset tempers the effects of poverty on academic achievement. Proceedings of the National Academy of Sciences 113, 31 (2016), 8664--8668.
[13]
Nicola Dell and Neha Kumar. 2016. The ins and outs of HCI for development. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 2220--2232.
[14]
Angela L Duckworth and David Scott Yeager. 2015. Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher 44, 4 (2015), 237--251.
[15]
Carol S Dweck. 2006. Mindset: The new psychology of success. Random House Incorporated.
[16]
Carol S Dweck. 2010. Even geniuses work hard. Educational Leadership 68, 1 (2010), 16--20.
[17]
Carol S Dweck and Allison Master. 2008. Self-theories motivate self-regulated learning. Motivation and self-regulated learning: Theory, research, and applications (2008), 31--51.
[18]
Carol S Dweck and Daniel C Molden. 2000. Self theories. Handbook of competence and motivation (2000), 122--140.
[19]
Carol S Dweck, Gregory M Walton, and Geoffrey L Cohen. 2014. Academic Tenacity: Mindsets and Skills that Promote Long-Term Learning. Bill & Melinda Gates Foundation (2014).
[20]
Carol S Dweck and David S Yeager. 2019. Mindsets: A View From Two Eras. Perspectives on Psychological Science (2019), 1745691618804166.
[21]
Jacquelynne S Eccles and Allan Wigfield. 2002. Motivational beliefs, values, and goals. Annual review of psychology 53, 1 (2002), 109--132.
[22]
UNESCO Institute for Statistics. 2016. The world needs almost 69 million new teachers to reach the 2030 education goals. Sustainable Development Goals UIS/FS/2016/ED/39, 39 (2016), 1--16.
[23]
UNESCO Institute for Statistics. 2018. One in five children, adolescents and youth is out of school. Sustainable Development Goals UIS/FS/2018/ED/48, 48 (2018), 1--13.
[24]
Dragan Gašević, Shane Dawson, and George Siemens. 2015. LetâĂŹs not forget: Learning analytics are about learning. TechTrends 59, 1 (2015), 64--71.
[25]
Rachel Glennerster, Michael Kremer, Isaac Mbiti, and Kudzai Takavarasha. 2011. Access and quality in the Kenyan education system: a review of the progress, challenges and potential solutions., 53 pages.
[26]
GSM Association. 2018. The Mobile Economy: Sub-Saharan Africa. https://www.gsma.com/mobileeconomy/sub-saharan-africa/
[27]
René F Kizilcec and Sherif Halawa. 2015. Attrition and achievement gaps in online learning. In Proceedings of the Second (2015) ACM Conference on Learning@ Scale. ACM, 57--66.
[28]
René F Kizilcec, Chris Piech, and Emily Schneider. 2013. Deconstructing disengagement: analyzing learner subpopulations in massive open online courses. In Proceedings of the third international conference on learning analytics and knowledge. ACM, 170--179.
[29]
René F Kizilcec and Andrew J Saltarelli. 2019. Psychologically Inclusive Design. In Proceedings of the SIGCHI conference on human factors in computing systems. ACM.
[30]
René F Kizilcec, Andrew J Saltarelli, Justin Reich, and Geoffrey L Cohen. 2017. Closing global achievement gaps in MOOCs. Science 355, 6322 (2017), 251--252.
[31]
René F Kizilcec and Emily Schneider. 2015. Motivation as a lens to understand online learners: Toward data-driven design with the OLEI scale. ACM Transactions on Computer-Human Interaction (TOCHI) 22, 2 (2015), 6.
[32]
Agnes Kukulska-Hulme. 2007. Introduction. In Mobile Learning. Routledge, 17--22.
[33]
Daniel C Moos and Roger Azevedo. 2009. Learning with computer-based learning environments: A literature review of computer self-efficacy. Review of Educational Research 79, 2 (2009), 576--600.
[34]
Karen D Multon, Steven D Brown, and Robert W Lent. 1991. Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. Journal of counseling psychology 38, 1 (1991), 30.
[35]
Laura Naismith, Peter Lonsdale, Giasemi N Vavoula, and Mike Sharples. 2004. Mobile technologies and learning. (2004).
[36]
Eleanor O'Rourke, Kyla Haimovitz, Christy Ballweber, Carol Dweck, and Zoran Popović. 2014. Brain points: a growth mindset incentive structure boosts persistence in an educational game. In Proceedings of the SIGCHI conference on human factors in computing systems. ACM, 3339--3348.
[37]
Eleanor O'Rourke, Erin Peach, Carol S Dweck, and Zoran Popovic. 2016. Brain points: A deeper look at a growth mindset incentive structure for an educational game. In Proceedings of the Third (2016) ACM Conference on Learning@ Scale. ACM, 41--50.
[38]
Frank Pajares. 1996. Self-efficacy beliefs in academic settings. Review of educational research 66, 4 (1996), 543--578.
[39]
David Paunesku, Gregory M Walton, Carissa Romero, Eric N Smith, David S Yeager, and Carol S Dweck. 2015. Mind-set interventions are a scalable treatment for academic underachievement. Psychological science 26, 6 (2015), 784--793.
[40]
Paul R Pintrich and Elisabeth V De Groot. 1990. Motivational and self-regulated learning components of classroom academic performance. Journal of educational psychology 82, 1 (1990), 33.
[41]
Justin Reich and José A Ruipérez-Valiente. 2019. The MOOC pivot. Science 363, 6423 (2019), 130--131.
[42]
Dale H Schunk. 1991. Self-efficacy and academic motivation. Educational psychologist 26, 3-4 (1991), 207--231.
[43]
Mike Sharples, Josie Taylor, and Giasemi Vavoula. 2010. A theory of learning for the mobile age. In Medienbildung in neuen Kulturräumen. Springer, 87--99.
[44]
Mark Sherer, James E Maddux, Blaise Mercandante, Steven Prentice-Dunn, Beth Jacobs, and Ronald W Rogers. 1982. The self-efficacy scale: Construction and validation. Psychological reports 51, 2 (1982), 663--671.
[45]
Victoria F Sisk, Alexander P Burgoyne, Jingze Sun, Jennifer L Butler, and Brooke N Macnamara. 2018. To what extent and under which circumstances are growth mind-sets important to academic achievement? Two meta-analyses. Psychological science 29, 4 (2018), 549--571.
[46]
John Traxler. 2009. Current state of mobile learning. Mobile learning: Transforming the delivery of education and training 1 (2009), 9--24.
[47]
John Traxler and Philip Dearden. 2005. The potential for using SMS to support learning and organisation in sub-Saharan Africa. In Proceedings of Development Studies Association Conference, Milton Keynes.
[48]
Allan Wigfield. 1994. Expectancy-value theory of achievement motivation: A developmental perspective. Educational psychology review 6, 1 (1994), 49--78.
[49]
Allan Wigfield and Jacquelynne S Eccles. 2000. Expectancy-value theory of achievement motivation. Contemporary educational psychology 25, 1 (2000), 68--81.
[50]
David Scott Yeager and Carol S Dweck. 2012. Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational psychologist 47, 4 (2012), 302--314.
[51]
David S Yeager, Gregory M Walton, Shannon T Brady, Ezgi N Akcinar, David Paunesku, Laura Keane, Donald Kamentz, Gretchen Ritter, Angela Lee Duckworth, Robert Urstein, et al. 2016. Teaching a lay theory before college narrows achievement gaps at scale. Proceedings of the National Academy of Sciences (2016), 201524360.
[52]
Barry J Zimmerman. 1995. Self-efficacy and educational development. Self-efficacy in changing societies (1995), 202--231.

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  1. Growth Mindset Predicts Student Achievement and Behavior in Mobile Learning

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    L@S '19: Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale
    June 2019
    386 pages
    ISBN:9781450368049
    DOI:10.1145/3330430
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 24 June 2019

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    Author Tags

    1. Africa
    2. Expectancy-value theory
    3. Learning Analytics
    4. Mindset
    5. Mobile Learning
    6. Self-efficacy

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    Overall Acceptance Rate 117 of 440 submissions, 27%

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    • (2023)The Use of SMS and Other Mobile Phone-based Messaging to Support Education at Scale: A Synthesis of Recent EvidenceProceedings of the Tenth ACM Conference on Learning @ Scale10.1145/3573051.3596172(282-286)Online publication date: 20-Jul-2023
    • (2023) An exploratory investigation into the factors related to EdTech use among Kenyan girls British Journal of Educational Technology10.1111/bjet.1330754:4(1006-1024)Online publication date: 20-Feb-2023
    • (2023)How can messaging apps, WhatsApp and SMS be used to support learning? A scoping reviewTechnology, Pedagogy and Education10.1080/1475939X.2023.220159032:3(275-288)Online publication date: 25-Apr-2023
    • (2023)Positive Artificial Intelligence in Education (P-AIED): A RoadmapInternational Journal of Artificial Intelligence in Education10.1007/s40593-023-00357-y34:3(732-792)Online publication date: 3-Aug-2023
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    • (2022)EdTech and Girls Education in Low- and Middle-Income Countries: Which Intervention Types Have the Greatest Impact on Learning Outcomes for Girls?Proceedings of the Ninth ACM Conference on Learning @ Scale10.1145/3491140.3528305(330-334)Online publication date: 1-Jun-2022
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    • (2022)Research on the Influencing Factors and Mechanisms of Math Learning Motivation on Online Learning EngagementBlended Learning: Engaging Students in the New Normal Era10.1007/978-3-031-08939-8_17(194-205)Online publication date: 19-Jun-2022
    • (2021)Gamification of Computer Programming Tasks to Promote the Growth Mind-Set in a Disadvantaged SchoolInternational Journal of Game-Based Learning10.4018/IJGBL.28782712:1(1-24)Online publication date: 26-Nov-2021
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