Qualitative Prospectus Template

2

Refining Adaptive Learning Technologies in Classroom Environments: A Methodological Approach

Guerline Pierre Joseph

Dr. Jacobs

GCU/Education

RES-831

8/14/2024

Refining Adaptive Learning Technologies in Classroom Environments: A Methodological Approach

In the course of my doctoral program, combined with the valuable comments from my peers, I have fine-tuned my dissertation focus to consider the integration of adaptive learning technologies in traditional classrooms. My initial focus was generally on educational technology. As I dug further into the literature and participated in scholarly debates, I realized the critical need to know how adaptive learning systems might be successfully applied to improve student outcomes while addressing the complexity of various learning needs. This process of improvement has guided me to a more focused investigation of the possibilities and difficulties adaptive learning technology available in K–12 and higher education environments offer. Discussions with my peers also underlined the need to address problems of equity and accessibility while using these technologies.

Refined Problem Statement

Based on this refined focus and the problem space identified in my previous work, I have formulated the following problem statement: "Currently, there is a lack of information on how effective use of the adaptive learning technologies can be integrated with face-to-face teaching to enhance student learning achievements and to meet individual learning needs in different contexts and subjects." This problem statement embodies the broad area of concepts that I want to address in my study regarding the implementation of adaptive learning technologies for learners and instructors.

Potential Methodology

I have decided to adopt a qualitative research approach in my proposed dissertation study. This choice is based on the nature of the study and the type of data that needs to be accumulated and used while solving the research problem.

Justification for Qualitative Methodology

To this end, the choice of a qualitative research method approach for this study is anchored on several considerations fundamental to the characteristics, the rigor of the research problem under investigation, and the depth of understanding needed to address it appropriately.

Firstly, the problem statement focuses more on the 'how' aspect of adopting adaptive learning technologies in classrooms. In this regard, the emphasized focus on processes, experiences, and contextual factors is consonant with the qualitative methods of research. According to Creswell and Poth (2024), qualitative research is especially appropriate when capturing phenomena in their natural contexts and understanding how the various individuals or groups construct the different phenomena.

Adaptive learning technologies, when implemented in classroom settings, engage different stakeholders (the students, instructors, and school leaders) and are affected by several factors (including school climate, technology support, and expectations of curricula). Therefore, there is a need for a qualitative approach that will enable the exploration of these various viewpoints and the manner in which technology intertwines with pedagogy. Kabudi et al. (2021) argue that qualitative research can generate in-depth contextual information that is particularly useful when exploring the paradigm of technology-enhanced learning.

Furthermore, the problem statement stresses the requirement to respond to 'diverse learner needs in different contexts of education.' Essentially, the choice of qualitative approach is justified by its focus on description and context, which would enable capturing the specificity of educational contexts and the experiences of learners and teachers. This is consistent with Harati et al.'s (2021) survey on students' experience and perception of adaptive learning systems, where the authors used the qualitative approach to identify significant factors that the quantitative view might not expose.

The use of qualitative methodology also fits the nature of the research problem as exploratory in nature. Since the extent to which adaptive learning technologies can be integrated into traditional classrooms is a relatively new research topic, qualitative research helps identify the primary themes and discuss the findings that might not have been anticipated in advance. Such flexibility is important, especially when analyzing modern learning technologies, as Gligorea et al. (2023) mentioned in their adaptive learning overview.

Justification for Not Selecting Quantitative Methodology

Adopting a quantitative methodology has its benefits, particularly in finding relationships and quantifying the results and trends, yet it is not fit for the current research problem. The main reason for not adopting a quantitative approach is that the problem has not been defined in terms of establishing the extent or degree of integration and the related factors but rather the identification of the process and the factors affecting it. According to Yin (2018), when the research questions involve the use of "how" and "why," qualitative methods of data collection are relevant in most cases.

Quantitative methods, on the other hand, are very good at identifying statistical correlations and hypothesis testing. However, they may not give a sufficient discussion of the issues surrounding the implementation of adaptive learning technologies in different classrooms. Since the relationships between technology, pedagogy, and learning contexts underpinning this research problem are complex, approaches grounded in qualitative research are more appropriate. Moreover, in many learning environments, the application of adaptive learning technologies is still in its infancy, which means there may not be enough metrics or large-scale examples to be used for quantitative analysis. In the review of adaptive learning progress and challenges identified by Li et al. (2021), the authors pointed out that many aspects of adaptive learning implementation are still in the exploratory phases so that qualitative approaches remain more appropriate for early investigations.

Quantitative research paradigms could conceivably be applied to assess the consequences of implementing adaptive learning technologies (e. g., tests, participation rates) but are not well-suited to examine the processes, issues, and conditions that define the integration of such technologies – an area of concern based on the problem statement.

Conclusion

Thus, the use of qualitative research methodology in the context of the current research problem is based on the need to study the processes under study and their contexts in detail, emphasizing multiple viewpoints on the subject. This approach is consistent with the exploratory character of the study and the requirement of obtaining data that would capture the contexts for which adaptive learning technologies are expected to be integrated into classroom settings. Although information obtained through quantitative methods is useful in many contexts of educational research, the current focus on how these technologies are best employed makes a qualitative method more appropriate for addressing the posed problem and providing meaningful knowledge to the field of educational technology and adaptive learning.

References

Creswell, J. W., & Poth, C. N. (2024).  Qualitative inquiry and research design: Choosing among five approaches. (5th Ed.) Sage publications.

Gligorea, I., Cioca, M., Oancea, R., Gorski, A. T., Gorski, H., & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, 13(12), 1216. https://doi.org/10.3390/educsci13121216

Harati, H., Sujo-Montes, L., Tu, C. H., Armfield, S. J., & Yen, C. J. (2021). Assessment and learning in knowledge spaces (ALEKS) adaptive system impacts students' perception and self-regulated learning skills. Education Sciences, 11(10), 603. https://doi.org/10.3390/educsci11100603

Kabudi, T., Pappas, I., & Olsen, D. H. (2021). AI-enabled adaptive learning systems: A systematic mapping of the literature.  Computers and Education: Artificial Intelligence,  2, 100017. https://doi.org/10.1016/j.caeai.2021.100017

Li, F., He, Y., & Xue, Q. (2021). Progress, challenges, and countermeasures of adaptive learning. Educational Technology & Society, 24(3), 238-255. https://doi.org/10.30191/ETS.202107_24(3).0017

Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.