Research Article
Tobias Alexander Bang Tretow-Fish, Md Saifuddin Khalid
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep496
ABSTRACT
Existing methods for software requirements elicitation, five-point Likert scales and voting methods for requirements prioritization, and usability and user experience evaluation methods do not enable prioritizing the learning analytics dashboard requirements. Inspired by management and product design field, this research applies Kano’s two-factor theory to prioritize the features of learning analytics dashboards (LADs) of adaptive learning platform (ALP) called RhapsodeTM learner, based on students’ perceived usefulness to support designers’ decision-making. Comparing usability and user experience methods for evaluating LAD features, this paper contributes with the protocol and a case applying Kano method for evaluating the perceived importance of the dashboards in ALP. The paper applies Kano’s two-factor questionnaire on the 13 LADs features of RhapsodeTM learner. Responses from 17 students are collected using a questionnaire, which is used to showcase the strength of the two-factor theory through five tabular and graphical techniques. Through these five tabular and graphical techniques, we demonstrate the application and usefulness of the method as designers and management are often carried away by the possibilities of insights instead of actual usefulness. The results revealed a variation in the categorization of LADs depending on the technique employed. As the complexity of the techniques increases, additional factors that indicate data uncertainty are gradually incorporated, clearly highlighting the growing requirement for data. In the case of RhapsodeTM learner platform, results based on the students responses show that 11 of 13 LADs being excluded due to low significance level in categorization (technique 1) and low response rate.
Keywords: adaptive learning platforms, Kano’s two-factor theory, learning analytics dashboard, design methods
Research Article
Kelly McKenna, Beth Pouska, Marcia C. Moraes, James E. Folkestad
CONT ED TECHNOLOGY, Volume 10, Issue 3, pp. 214-228
ABSTRACT
Accessible learning analytics available from the data within learning management systems, can assist with teaching and learning practices, but often this data is difficult to interpret. Learning analytics, specifically those presented in visual-form, can provide information that supports learners’ reflection and guides them to the necessary changes that lead to successful self-regulated learning. This research study utilized photo-elicitation methods to prompt learners’ reflections of their self-regulated retrieval practice activities, quiz-based learning opportunities, which were qualitatively analyzed. A tool, U-Behavior, was created which was designed to extract students attempt data on the retrieval practice activities which were presented to students as opportunities to study the course content rather than as evaluations of understanding. Upon completion of the retrieval practice activities, learners were presented with their personalized learning analytics in visual-form and prompted to reflect on their learning. Visual-form learning analytics create opportunities for feedback and critical reflection for both instructors and learners and improve student learning. Analysis of the visual-form learning analytics and corresponding reflections highlighted learners’ understanding of high-impact learning practices, the realization of intended study behaviors versus engrained behaviors, high score orientation, and a focus on comparisons.
Keywords: Learning analytics, Visualizations, Reflection
Research Article
Barton K. Pursel, Hui Xie
CONT ED TECHNOLOGY, Volume 5, Issue 2, pp. 96-109
ABSTRACT
As social and collaborative technologies emerge, educators and scholars continue to explore and experiment with how these tools might impact pedagogy. For over a decade, educators experimented with the use of blogs in academic settings, a tool that allows for students and instructors to enter into a rich dialogue. With most technology tools, users often leave ‘digital footprints’ throughout the environment. These footprints, in combination with other sources of data, allow researchers to explore relationships between the tool itself and the different types of end users. This study examines two years of institutional blog data, combined with demographic data to help describe the users of a blog platform. Different clusters of users are uncovered, and various use cases are explored, illustrating how different instructors choose to leverage blogs in the flow of a course. Using analysis of variance (ANOVA) to compare different blogging groups, results show a strong correlation between entry-dominant bloggers and growth in Grade Point Average (GPA) over time. With the rise in popularity of learning analytics, the results of this study might influence future learning analytics tools and systems
Keywords: Blogs, Weblogs, Learning analytics, Online pedagogy