Navigating the Integration of Mobile Learning for Enhanced Course Personalization

ErasmusX
7 min readApr 8, 2024

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Written by Daria Ilishkina, researcher at ErasmusX | Image by Tirachard Kumtanom

Personalizing a course to the unique needs of 30 students is challenging, let alone for 300 or more. Then how can educators adapt a course in a way that doesn’t require significant investments in resources for creating and managing individualized learning trajectories? The integration of mobile learning (m-learning) into the curriculum presents a compelling strategy. A technology-based curriculum sometimes shows promising results in helping students learn (Schleisman et al., 2018).

M-learning facilitates education through smartphones and tablets, predominantly through specialized applications. This approach typically embraces micro-learning, encouraging students to engage in concise sessions that allow for the incremental absorption of compact, digestible content pieces.

The benefits of m-learning

Several advantages of m-learning position it as a promising strategy for course personalization:

  • Integration into daily life mobile devices are firmly woven into our daily routine, making smartphone interactions familiar and comfortable for learners (Eynon, 2021);
  • Accessibility — micro-learning offers students the flexibility to learn at times, places, and speeds that align with their needs and bustling lifestyles (Bernacki et al., 2020; Yuskovych-Zhukovska et al., 2022);
  • Potential for micro-learning — sometimes students do not have enough time and energy for a big assignment, but they could have enough for a small one — m-learning could be this small alternative.
  • Enhances learning skills — m-learning has shown potential in enhancing students’ self-regulated learning skills and motivation to learn (Mascret et al., 2023; Palalas & Wark, 2020; Wei et al., 2022).

In sum, m-learning represents a forward-thinking approach to curriculum development, promising enhanced accessibility, individualization, and adaptability.

The challenges of m-learning

Nonetheless, m-learning comes with its set of challenges. For educators, key issues include an escalated workload, the emergence of ‘tech stress’, dependence on their willingness to enhance personal competencies, their conviction in technology’s educational value, and the essential technological pedagogical content knowledge for m-learning’s efficacious integration (Hossain et al., 2021; Lindín et al., 2022; Mascret et al., 2023).

Students, on their part, might encounter challenges related to task-switching, lack of skills needed for autonomous learning, and skepticism towards technology’s educational value (Moca & Badulescu, 2023; Joshi et al., 2022; Yuskovych-Zhukovska et al., 2022). Notably, the limitations in educational outcomes achievable via m-learning highlight the critical need for its strategic integration into the curriculum, ensuring the maximization of its benefits.

The following paragraphs suggest considering a course through the activity theory as a system of actions, tools, beliefs, and rules, all orchestrated to support participants in reaching learning goals. This perspective can help assess the potential for integrating an m-learning app into the curriculum.

Actions and tools

Integrating m-learning into the curriculum represents a strategic opportunity to either replace outdated learning actions and tools or supplement them with new ones. The first step of analyzing how to integrate m-learning is to thoroughly assess the course’s current learning actions and tools that define the course structure:

  • What are the course learning goals?
  • What are students expected to do to achieve the course goals?
  • What tools help them to perform these learning actions?

Typically, students are expected to deploy study skills, such as engaging in reflective thinking guided by specific questions. They are also expected to apply subject-specific skills, for example, performing statistical analyses in the “R” software on a laptop. Considering the variance in students’ study and subject-specific skills, m-learning emerges as an invaluable aid for accommodating students with differing proficiency levels.

Students exhibit diverse study skills, which are crucial for their success in the course. Integrating mobile apps that focus on these can allow students to master the essential study skills required for the course. For instance, courses with numerous peer-learning activities encourage students to update their knowledge by collaborating with peers. The ACE Yourself app is a valuable resource for different study skills.

Reflection is another critical area — students are usually expected to think about their learning journey and reflect on their experiences. However, class time might not always allow for reflection, leading to its neglect post-class. Suggesting an app like Reflectly, which nudges students towards reflection and records their thoughts for future reference, may address this gap effectively.

Students’ varying levels of subject knowledge and difference in course progression highlight the need for personalized educational support. For example, utilizing subject-specific apps like Brilliant can provide students an opportunity to get alternative explanations or additional practice that complement the course content. Occasionally, one might realize that the specific application that is needed does not exist. This could be a good reason to contact the university’s innovation department and consider creating it!

Overall, there are three variants of how m-learning could be added to the course. Each variant will cause different effects on the course’s load:

  1. Substitute outdated and inefficient actions and tools by incorporating m-learning as a compulsory element of the curriculum;
  2. Introduce new actions and tools, resulting in an expanded course;
  3. Incorporate new actions and tools by integrating m-learning as an optional curriculum component, expanding the course for students who opt for this additional route.

Implementing m-learning as an optional curriculum component can be a secure platform for introducing new technologies and observing student feedback. Moreover, it offers students a chance to enhance their skills or bridge knowledge gaps left by the main curriculum, thereby enriching the personalization of the course. However, be aware that when the mobile app is separate from the mandatory curriculum, students could consider it redundant if everything is already planned (Baars et al., 2022).

Beliefs

After considering actions and tools that constitute the course, analyze the learners’ and teachers’ perceptions of m-learning. These beliefs and perceptions can either enhance engagement with or serve as obstacles to adopting new technologies. Sometimes, students are skeptical about technology’s relevance and efficacy in enhancing their educational experience. Initiating an open conversation about the app’s anticipated advantages and potential drawbacks could encourage its adoption. This skepticism is not isolated to students alone; educators’ perspectives towards m-learning bear significant weight in its successful integration.

Investigating its scientific basics may provide much-needed assurance for those harboring doubts about the app. For instance, the ACE Yourself app’s initial version was designed around the principles of self-regulated learning theory. Furthermore, the app’s effectiveness has been empirically tested, with findings from the first version published (Baars et al., 2022) and outcomes from the second version expected shortly. While there is no ideal app, being aware of all the pros and cons can help one consider participants’ beliefs and integrate the app smoothly.

Rules

The final step is to consider the rules that underpin relationships between participants and the course itself. These rules serve as the connective tissue linking participants with the intended goals, actions, and tools provided. While specific rules are explicitly communicated, such as the criteria for successful course completion, others remain indistinct, like directives for peer collaboration without detailed instructions. A notable barrier to app adoption among students is the lack of explicit guidance regarding its application. So, it is critical to clarify the app’s function within the course to students, regardless of how it is integrated (Baars et al., 2022).

The integration of mobile learning (m-learning) offers a compelling path toward personalized education, blending technology with individual learner needs. While challenges exist, the vision of a more adaptable, accessible, and tailored learning experience drives us forward.

References

Baars, M., Khare, S., & Ridderstap, L. (2022). Exploring students’ use of a mobile application to support their self-regulated learning processes. Frontiers in Psychology, 13, 793002.

Bernacki, M. L., Greene, J. A., & Crompton, H. (2020). Mobile technology, learning, and achievement: Advances in understanding and measuring the role of mobile technology in education. Contemporary Educational Psychology, 60, 101827.)

Dolowitz, A., Collier, J., Hayes, A., & Kumsal, C. (2023). Iterative Design and Integration of a Microlearning Mobile App for Performance Improvement and Support for NATO Employees. TechTrends, 67(1), 143–149.

Eynon, R. (2021). Becoming digitally literate: Reinstating an educational lens to digital skills policies for adults. British Educational Research Journal, 47(1), 146–162. https://doi-org.mu.idm.oclc.org/10.1002/berj.3686

Hossain, S. F. A., Nurunnabi, M., & Hussain, K. (2021). Continuous mobile devices usage tendency in the TPACK-based classroom and academic performance of university students. Technology, Pedagogy and Education, 30(4), 589–607.

Joshi, S. C., Woodward, J., & Woltering, S. (2022). Cell phone use distracts young adults from academic work with limited benefit to self-regulatory behavior. Current Psychology, 1–17.

Lindín, C., Steffens, K., & Bartolomé, A. (2022). Experiencing Edublocks: A Project to Help Students in Higher Education to Select Their Own Learning Paths. Journal of Interactive Media in Education, 2022(1).

Mascret, N., Marlin, K., Laisney, P., Castéra, J., & Brandt-Pomares, P. (2023). Teachers’ acceptance of an open-source, collaborative, free m-learning app: The predictive role of teachers’ self-approach goals. Education and Information Technologies, 1–29.

Moca, M., & Badulescu, A. (2023). Determinants of Economical High School Students’ Attitudes toward Mobile Devices Use. Sustainability, 15(12), 9331.

Palalas, A., & Wark, N. (2020). The relationship between mobile learning and self-regulated learning: A systematic review. Australasian Journal of Educational Technology, 36(4), 151–172.

Schleisman, K. B., Selcen Guzey, S., Lie, R., Michlin, M., Desjardins, C., Shackleton, H. S., … & Dubinsky, J. M. (2018). Learning neuroscience with technology: a scaffolded, active learning approach. Journal of science education and technology, 27, 566–580.

Yuskovych-Zhukovska, V., Bogut, O., Lotyuk, Y., Kravchuck, O., Rudenko, O., & Vasylenko, H. (2022). E-Learning in a Postmodern Society. Postmodern Openings, 13(1 Sup1), 447–464.

Wei, D., Talib, M. B. A., & Guo, R. (2022). A Systematic Review of Mobile Learning and Student’s Self-Regulated Learning. Eurasian Journal of Educational Research, 102(102), 233–252

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