Boelens, R., De Wever, B., & Voet, M. (2017). Four key challenges to the design of blended learning: A systematic literature review. Educational Research Review, 22, 1–18. https://doi.org/10.1016/j.edurev.2017.06.001
In this article, the authors conducted a systematic review, analyzing the included studies on the basis of 4 design factors used in blended environments. These factors are: incorporating flexibility, stimulating interaction, facilitating students’ learning processes, and fostering an affective learning climate. The authors chose these categories based on current and most-cited literature on blended learning environments. 20 articles were ultimately selected for inclusion in the review. Results showed little attention to flexibility of the blend in terms of learner autonomy, as well as little attention to affective learning environments. Interaction and facilitating student learning are more commonly addressed in face-to-face and online environments respectively.
This review adopted the recommendations of the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) statement to conduct the review. Using an existing tool identified and validated in the literature strengthens the inclusion and exclusion decisions for the review. The analysis of articles by the 4 identified factors adds a novel element generated by the authors but also rooted in the literature. Descriptions are exhaustive but remain concise.
I found this research useful in providing a view of current research in blended learning environments. By examining though the four-part framework, the authors supply context to the studies included, beyond simple frequency counts. As I explore various topics to investigate in my own research, it is useful for gaps in the literature to be provided clearly based on accepted criteria provided.
Järvenoja, H., Järvelä, S., & Malmberg, J. (2017). Supporting groups’ emotion and motivation regulation during collaborative learning. Learning and Instruction.
This research utilized a technological tool, called the S-REG application to measure learner’s individual self-reported motivation and emotional states and also provide feedback to collaborative groups of learners. These data were collected along with qualitative data in the form of video recordings. Data were used to answer questions pertaining to group regulation especially manifestations of co-regulation versus shared regulation in collaborative groups.
The conceptual framework is well defined in this study, including description of relevant gaps in the literature. While studies of regulation are frequent for individuals, they are less so for groups. The differences between co-regulation and shared regulation are clearly described, providing context for the results and discussion. Additionally, the incorporation of a novel technological tool adds a practical, tangible element to the study.
This study is relevant to my work in that I believe the study of self-regulation is integral to understanding engagement in online and blended learning environments. While this environment was not online, the investigation of collaborative group regulation is fascinating and as vitally relevant as the study of individual self-regulation. Most useful to me is the opportunity to broaden my internal schema of SRL to include the study of regulation in collaborative groups – a facet of study unfamiliar to me.
Vanslambrouck, S., Zhu, C., Lombaerts, K., Philipsen, B., & Tondeur, J. (2018). Students’ motivation and subjective task value of participating in online and blended learning environments. The Internet and Higher Education, 36, 33–40. https://doi.org/10.1016/j.iheduc.2017.09.002
This research examined the value and costs that students attribute to online and blended environments. It was a mixed methods study, with survey data providing the qualitative portion and structured interviews providing the qualitative data. There are 4 research questions addressed, all related to motivational profiles of students. These include how profiles can be identified, how students attribute value to participation, which values are attributed to online and blended learning and which to education in general, and if there is a link between specific motivational profiles and subjective values. Data were analyzed by combining measures informed by 3 elements of the conceptual framework developed. These are self-determination theory, expectancy-value theory and various research on motivational profiles. Results indicate the relationship of motivational profile and perception of value provide opportunities to personalize orientation and teaching based on motivational profile.
Particularly strong in this research is the design of the conceptual framework. The authors synthesize three major areas of motivational theory developing measures to creatively assess relationships. The primary quantitative measure was a well-established survey, testing in the adapted Dutch language for reliability. The incorporation of accepted frameworks to address motivation on multiple levels is common throughout the work. The discussion of student-perceived costs to participation in blended environments is instructive as well.
This research is important to me in that it provides a glimpse into several ideas from motivational theory I was not familiar with. While I have looked at SDT, expectancy-value theory and motivational profiles were fairly new. I plan to take a look at both to further build a personal framework of ideas related to online motivation and self-directed learning.