Developing a Classification System to Help Educators choose Mobile Applications that match their Pedagogy (TPK: Technology-Pedagogical Knowledge)

Concurrent Session 5
Streamed Session

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Session Materials

Brief Abstract

This interactive education session focuses on helping simplify the TPK part of the TPACK model by classifying mobile apps by pedagogical decisions. Apps will be presented by pedagogy and a live discussion will occur in Google Hangouts during the session. Attendees will access documents via a Google Folder. 


Dr. Kelly S. Rippard is a researcher of English and pre-service teacher education, instructional design, curriculum development, problem-based instructional models, technology education, and blended learning. After having a successful career as a secondary and postsecondary English educator as well as an instructional designer and curriculum specialist, Dr. Rippard is currently a lecturer in the department of teaching and learning at Old Dominion University in Norfolk, VA. Here she teaches future teachers about educational methods and technology in both traditional and online classrooms.

Extended Abstract


While the rise in mobile applications is hard to track due to the fast-paced nature of the technology, it has been estimated that there are approximately 2.8 million Google apps and 2.2 billion Apple apps as of 2017 (“Mobile App Usage - Statistics & Facts”). One fact that is apparent, though, is that mobile applications accessed and used on phones and tablets have become a big part of the 21st century person’s life, including that of students. Indeed, Burns-Sardone (2014) notes that the Bring-Your-Own-Device (BYOD) policies from the business world have spread to the PK-12 environment as well, offering schools and teachers an easier way to make use of both the Internet and technology. Researchers such as McLean (2016), Song (2014), and Jeng, Wu, Huang, Tan, and Yang (2010) have all written about the ways mobile applications and BYOD can be beneficial to both the educator and student, offering innovative ways to facilitate learning. However, what is missing in much of the research is the information about when educators should use different mobile applications within their lessons.

Some researchers have begun to try to develop a system to classify mobile apps based upon their “purpose, content, and value” (see Cherner, Dix, & Lee, 2014) while others have sought to develop rubrics and templates to help subject-specific educators choose and classify apps (see Green, Hechter, Tysinger, & Chassereau, 2014). Neither of these systems helps educators choose apps by pedagogy or the part of the lesson they are focusing on. Many educators, new and experienced, may struggle with knowing which mobile apps to use at which point in their lessons since the limited research available focuses more on types of tasks (e.g. presentation, collaboration) or content (e.g. science, math, English). This struggle may, in turn, lead to a poor matching between the technology and pedagogy. As the TPACK model for technology integration in education suggests, in order to increase motivation and make content more accessible to students, educators should try to make sure their technology and pedagogy align.


Therefore, this proposed education session seeks to add to the growing body of research on mobile apps in education by sharing the researcher’s current work, which is the creation of a table of free mobile applications mapped to pedagogical decisions. There are two goals for this session. The first goal is to share this information with both online and blended educators as well as various educational specialists (e.g. instructional designers) so that they can use the information to make sure their mobile application choice and pedagogy align in a technology-enhanced classroom, increasing the TPK part of the TPACK model. The second goal is to discuss the information with colleagues and discuss revisions, editions, and future research.

Session Content:

The presenter will use the Canva application via an iPad to lead the educational session’s presentation on free mobile applications classified by pedagogical decisions. Session attendees will be given a address and a QR Code that they can use to access the presenter’s Google Drive folder, which will house both a .PDF copy of the Canva presentation and a copy of the mobile application-pedagogy table. Attendees will also be given the name of a Google Hangouts group they can join during the session. The session will be led by four guiding questions: 1) How do we currently classify web tools and mobile apps? 2) What are the common key terms for these classifications? 3) Should systems of classification be based on a common model of a lesson such as the Madeline Hunter’s model (1982): anticipatory set, input, modeling, checking for understanding, direct instruction, guided practice, independent practice, closure? 4) What would a system of classification using a pedagogical model look like?

Following the fourth question, the presentation will demonstrate what a system of classification based upon the TPK: Technology-Pedagogical Knowledge would look like. This would include the eight parts of a lesson: the anticipatory set, input, modeling, checking for understanding, direct instruction, guided practice, independent practice, and closure. Each part would include the researcher’s “BEST TWO”, which are two free mobile applications educators could use during a specific pedagogical part. All applications will be modeled via the researcher’s iPad. For example, the free Poll Everywhere app (available on Apple and Android devices) can be used by educators as part of the anticipatory set since users can activate prior knowledge by sharing their knowledge or understanding of a given topic. 

Throughout the session, the presenter will ask attendees to live share their thoughts, comments, and questions via a Google Hangouts group called TPK Mobile Apps. The join link will be provided to guests at the start of the session and the presenter will integrate thoughts, comments, and questions during the session.  The end of the presentation will include time to discuss improvements to the system of classification, additional mobile apps, as well as directions for future research. 





Burns-Sardone, N. (2014). Making the case for BYOD instruction in teacher education. Issues in Informing Science and Information Technology11(1), 192-200.

Cherner, T., Dix, J., & Lee, C. (2014). Cleaning up that mess: A framework for classifying educational apps. Contemporary Issues in Technology and Teacher Education14(2), 158-193.

Green, L. S., Hechter, R. P., Tysinger, P. D., & Chassereau, K. D. (2014). Mobile app selection for 5th through 12th grade science: The development of the MASS rubric. Computers & Education75, 65-71.

Hunter, M. C. (1982). Mastery teaching. Thousand Oaks, CA: Corwin Press.

Jeng, Y. L., Wu, T. T., Huang, Y. M., Tan, Q., & Yang, S. J. (2010). The add-on impact of mobile applications in learning strategies: A review study. Educational Technology & Society13(3), 3-11.

McLean, K. J. (2016). The implementation of bring your own device (BYOD) in primary [elementary] schools. Frontiers in psychology7.

“Mobile App Usage - Statistics & Facts”. (2017). Retrieved from

Song, Y. (2014). “Bring Your Own Device (BYOD)” for seamless science inquiry in a primary school. Computers & Education74, 50-60.