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Identifying quality educational apps: Lessons from ‘top’ mathematics apps in the Apple App store

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Abstract

There are 80,000+ educational apps in the Apple App Store and math apps are the most common. We searched for ‘math’ in the education category and selected the top 10 apps for each of the 3 filters provided by Apple (Relevance, Popularity, Rating) and 3 age categories (0–5, 6–8, 9–11). Using these top 90 apps, we examined the basic information (e.g., price), educational content, and user ratings to see whether the information provided in app stores helps parents and educators find quality educational apps. There was a surprising lack of transparency and meaningful information. The Apple App store needs to explain how it selects ‘top’ apps and developers need to provide benchmarks of educational quality in their app descriptions.

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Notes

  1. For each math app, every app image provided in the app store was downloaded and used to calculate the average pixels per byte for that app. This was done by a) dividing the total number of pixels in each app image (e.g., 1020 X 1980 image = 2019.600 pixels) by its file size (bytes) and b) determining the average pixels per byte across each app’s set of images. The logic of the pixels per byte measure is that computer image compression produces larger sized images when there are more differences between pixels. If pixels are similar then an image is less complex (e.g., a solid blue picture has no differences between pixels) and it requires fewer bytes to encode that information. Thus the pixels per byte of data is inversely related to complexity such that the fewer number of pixels generated per byte the more complex the image.

References

  • Anastasiou, D., & Gupta, R. (2011). Comparison of crowdsourcing translation with machine translation. Journal of Information Science, 37, 637–659.

    Article  Google Scholar 

  • AppCensus. (2019). AppCensus: Learn the privacy cost of free apps. Retrieved Jan 9, 2019, from https://appcensus.mobi

  • Berliner, D. C. (2013). Inequality, poverty, and the socialization of America’s youth for the responsibilities of citizenship. Theory Into Practice, 52(3), 203–209.

    Article  Google Scholar 

  • Callaghan, M. N., & Reich, S. M. (2018). Are educational preschool apps designed to teach? An analysis of the app market. Learning, Media and Technology, 43(3), 280–293.

    Article  Google Scholar 

  • Carare, O. (2012). The impact of bestseller rank on demand: Evidence from the app market. International Economic Review, 53, 717–742.

    Article  MATH  Google Scholar 

  • Cayton-Hodges, G. A., Feng, G., & Pan, X. (2015). Tablet-based math assessment: What can we learn from math apps? Educational Technology & Society, 18(2), 3–20.

    Google Scholar 

  • Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: What have we learned in 60 years? Frontiers in Psychology, 7(1333), 385–416. https://doi.org/10.3389/fpsyg.2016.00508.

    Article  Google Scholar 

  • Dubé, A. K., & Alam, S. S., Xu, C., Wen, R., & Kacmaz, G. (2019). Tablets as elementary mathematics education tools: A review of research and theory. In K. M. Robinson, D. Kotsopolous, & H. Osana (Eds), Interdisciplinary perspectives on early mathematical minds. Springer International Publishing.

  • Fabian, K., Topping, K. J., & Barron, I. G. (2016). Mobile technology and mathematics: Effects on students’ attitudes, engagement, and achievement. Journal of Computers in Education, 3(1), 77–104.

    Article  Google Scholar 

  • Imbo, I., & LeFevre, J.-A. (2009). Cultural differences in complex addition: Efficient Chinese versus adaptive Belgians and Canadians. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(6).

  • Ke, F., & Kwak, D. (2013). Online learning across ethnicity and age: A study on learning interaction participation, perception, and learning satisfaction. Computers & Education, 61, 43–51.

    Article  Google Scholar 

  • Knotko, L. (2018). The ultimate guide to app store screenshots: Size, styles, tips and ASO best practices. Retrieved Jan 8, 2019, from https://splitmetrics.com/blog/app-store- screenshots-Aso-guide/.

  • Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621.

    Article  MATH  Google Scholar 

  • Lamont, M., & Small, M. L. (2010). Cultural diversity and anti-poverty policy. International Social Science Journal, 61(199), 169–180.

    Article  Google Scholar 

  • Larkin, K., & Calder, N. (2016). Mathematics education and mobile technologies. Journal of Mathematics Educational Research, 28, 1–7.

    Article  Google Scholar 

  • Lee, G., & Raghu, T. (2014). Determinants of mobile apps’ success: Evidence from the app store market. Journal of Management Information Systems, 31, 133–170.

    Article  Google Scholar 

  • LeFevre, J.-A., Penner-Wilger, M., Pyke, A. A., Shanahan, T., & Deslauriers, W. A. (2014). Putting two and two together: Declines in arithmetic fluency among young Canadian adults, 1993 to 2005. CogSciTechReports,1–8.

  • Liao, C. C., Chen, Z.-H., Cheng, H. N., Chen, F.-C., & Chan, T.-W. (2011). My-mini-pet: A handheld pet- nurturing game to engage students in arithmetic practices. Journal of Computer Assisted Learning, 27(1), 76–89.

    Article  Google Scholar 

  • Main, S., & O’Rourke, J. (2011). New directions for traditional lessons: Can handheld game consolesenhance mental mathematics skills? Australian Journal of Teacher Education, 36(2), 4.

    Article  Google Scholar 

  • McEwen, R., & Dubé, A. K. (2017). Understanding tablets from early childhood to adulthood: Encounters with touch technology. New York: Routledge.

    Book  Google Scholar 

  • Musti-Rao, S., & Plati, E. (2015). Comparing two classwide interventions: Implications of using technology for increasing multiplication fact fluency. Journal of Behavioral Education, 24, 418–437. https://doi.org/10.1007/s10864-015-9228-x.

  • Peachey, N. (2013). Criteria for evaluating web tools and apps. Retrieved from: https://nikpeachey.blogspot.co.uk/2013/04/criteria-for-evaluating-web-tools-and.html.

  • Reiti, J. (2014). Ontario announces $150 million investment for iPads in the classroom. Retrieved Jan 24, 2017, from http://www.cbc.ca/news/canada/hamilton/ontario-announces-150-million-investment-for-ipads-in-the-classroom-1.2755755.

  • Rosell-Aguilar, F. (2017). State of the app: A taxonomy and framework for evaluating language learning mobile applications. Computer Assisted Language Instruction Consortium, 34, 243–258.

    Google Scholar 

  • Schrock, K. (2013). Critical evaluation of mobile apps. Retrieved from http://www.ipad- s4teaching.net/uploads/3/9/2/2/392267/evalipad_content.pdf.

  • Schuler, C. (2012). Ilearn ii: An analysis of the education category of the itunes app store. New York: The Joan Ganz Cooney Center at Sesame Workshop.

    Google Scholar 

  • Stevenson, I. (2008). Tool, tutor, environment or resource: Exploring metaphors for digital technology and pedagogy using activity theory. Computers & Education, 51, 836–853. https://doi.org/10.1016/j.compedu.2007.09.001.

  • Tawfik, A. A., Reeves, T. D., & Stich, A. (2016). Intended and unintended consequences of educational technology on social inequality. TechTrends, 60, 598–605.

    Article  Google Scholar 

  • Vaala, S., Ly, A., & Levine, M. H. (2015). Getting a read on the app stores: A market scan and analysis of children’s literacy apps. New York. Retrieved from https://eric.ed.gov/?id=ED574396

  • Vincent, T. (2012). Ways to evaluate educational apps. Retrieved from http://learningin-hand.com/blog/ways-to-evaluate-educational-apps.html.

  • Volk, M., Cotic, M., Zajc, M., & Starcic, A. I. (2017). Tablet-based cross-curricular maths vs. traditional maths classroom practice for higher-order learning outcomes. Computers & Education, 114, 1–23.

    Article  Google Scholar 

  • Walker, H. (2011). Evaluating the effectiveness of apps for mobile devices. Journal of Special Education Technology, 26(4), 59–63.

    Article  Google Scholar 

  • Wang, M., & Li, X. (2017). Effects of the aesthetic design of icons on app downloads: Evidence from an android market. Electronic Commerce Research, 17, 83–102.

    Article  Google Scholar 

  • Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics Bulletin, 1(6), 80–83.

    Article  Google Scholar 

  • Wu, L. J., Hsiao, H. S., Chang, K. E., & Sung, Y. T. (2006). Construct mathematic path and interactive problem solving discussion system in Mobile learning environment. In proceeding of the IADIS International Conference on Mobile Learning, 2006. Dublin, Ireland (pp. 288–292).

  • Yang, E. F. Y., Chang, B., Cheng, H. N. H., & Chan, T. (2016). Improving pupils’ mathematical communication abilities through computer - supported reciprocal peer tutoring. Educational Technology & Society, 19(3), 157–169.

    Google Scholar 

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Source data used for this study can be found on the authors’ website.

Funding details

funding for this work was provided by the Social Sciences and Humanities Research Council of Canada (430–2017-00230).

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Authors and Affiliations

  1. McGill University, Montreal, Quebec, H3A 0G4, Canada

    Adam Kenneth Dubé, Gulsah Kacmaz, Run Wen, Sabrina Shajeen Alam & Chu Xu

  2. Department of Educational & Counselling Psychology, 3700 McTavish Street, Montreal, QC, H3A 1Y2, Canada

    Adam Kenneth Dubé

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  1. Adam Kenneth Dubé
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  2. Gulsah Kacmaz
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Correspondence to Adam Kenneth Dubé.

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Dubé, A.K., Kacmaz, G., Wen, R. et al. Identifying quality educational apps: Lessons from ‘top’ mathematics apps in the Apple App store. Educ Inf Technol 25, 5389–5404 (2020). https://doi.org/10.1007/s10639-020-10234-z

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