Demographical Changes of Student Subgroups in MOOCs: Towards Predicting At-Risk Students

Past studies have shown that student engagement in Massive Open Online Courses (MOOCs) could be used to identify at-risk students (students with drop-out tendency). Some studies have further considered student diversity by looking into subgroup behavior. Yet, most of them lack consideration of students’ behavioral changes along the course. Towards bridging the gap, this study clusters students based on both their interaction with the system and their characteristics and explores how their cluster membership changes along the course. The result shows that students’ cluster membership changes significantly in the first half of the course and stabilized in the second half of the course. Our findings provide insight into how students may be engaged in learning on MOOC platforms and suggest the improvement of identifying at-risk students based on their temporal data

Teaching Interactive Fiction for Undergraduate Students with the Aid of Information Technologies: An Experience Report

This paper presents an experience report concerning the use of a platformcalled “Storium” in the subject of “Interactive Fiction” for undergraduatestudents, from a Digital Design Course. The objective was to use the learningtheories of constructivism and multimedia learning to create an instructionalplan devised to teach the students how to create complex interactive narrativesand stories from a practical perspective. During the course, the students learnedthe subject’s theoretical concepts and applied them directly, creating their owninteractive fiction. The results from this research proposes a new approach, usingdigital tools whose resources provides an environment for the creation ofinteractive narratives. These narratives can be used to aid future designs ofinstructional plans for complex writing concepts

Does gamification affect flow experience? A systematic literature review

In recent years, studies in different areas have used gamification to improve users' flow experience. However, due to the high variety of the conducted studies and the lack of secondary studies (e.g., systematic literature reviews) in this field, it is difficult to get the state-of-the-art of this research domain. To address this problem, we conducted a systematic literature review to identify i) which gamification design methods have been used in the studies about gamification and Flow Theory, ii) which gamification elements have been used in these studies, iii) which methods have been used to evaluate the users' flow experience in gamified settings, and iv) how gamification affects users' flow experience. The main results show that there is growing interest to this field, as the number of publications is increasing. The most significant interest is in the area of gamification in education. However, there is no unanimity regarding the preferred method of the study or the effects of gamification on users' experience. Our results highlight the importance of conducting new experimental studies investigating how gamification affects the users' flow experience in different gamified settings, applications and domains.Comment: 5th International GamiFIN Conference 2021 (GamiFIN 2021), April 7-10, 2021, Finlan

The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation

Massive Online Open Course (MOOC) platforms are considered a distinctive way to deliver a modern educational experience, open to a worldwide public. However, student engagement in MOOCs is a less explored area, although it is known that MOOCs suffer from one of the highest dropout rates within learning environments in general, and in e-learning in particular. A special challenge in this area is finding early, measurable indicators of engagement. This paper tackles this issue with a unique blend of data analytics and NLP and machine learning techniques together with a solid foundation in psychological theories. Importantly, we show for the first time how Self-Determination Theory (SDT) can be mapped onto concrete features extracted from tracking student behaviour on MOOCs. We map the dimensions of Autonomy, Relatedness and Competence, leading to methods to characterise engaged and disengaged MOOC student behaviours, and exploring what triggers and promotes MOOC students’ interest and engagement. The paper further contributes by building the Engage Taxonomy, the first taxonomy of MOOC engagement tracking parameters, mapped over 4 engagement theories: SDT, Drive, ET, Process of Engagement. Moreover, we define and analyse students’ engagement tracking, with a larger than usual body of content (6 MOOC courses from two different universities with 26 runs spanning between 2013 and 2018) and students (initially around 218.235). Importantly, the paper also serves as the first large-scale evaluation of the SDT theory itself, providing a blueprint for large-scale theory evaluation. It also provides for the first-time metrics for measurable engagement in MOOCs, including specific measures for Autonomy, Relatedness and Competence; it evaluates these based on existing (and expanded) measures of success in MOOCs: Completion rate, Correct Answer ratio and Reply ratio. In addition, to further illustrate the use of the proposed SDT metrics, this study is the first to use SDT constructs extracted from the first week, to predict active and non-active students in the following week

Nonlinear management of the angular momentum of soliton clusters

We demonstrate an original approach to acquire nonlinear control over the angular momentum of a cluster of solitary waves. Our model, derived from a general description of nonlinear energy propagation in dispersive media, shows that the cluster angular momentum can be adjusted by acting on the global energy input into the system. The phenomenon is experimentally verified in liquid crystals by observing power-dependent rotation of a two-soliton cluster.Comment: 4 pages, 3 figure

Analysing Gamification Elements in Educational Environments Using an Existing Gamification Taxonomy

Gamification has been widely employed in the educational domain over the past eight years when the term became a trend. However, the literature states that gamification still lacks formal definitions to support the design and analysis of gamified strategies. This paper analysed the game elements employed in gamified learning environments through a previously proposed and evaluated taxonomy while detailing and expanding this taxonomy. In the current paper, we describe our taxonomy in-depth as well as expand it. Our new structured results demonstrate an extension of the proposed taxonomy which results from this process, is divided into five dimensions, related to the learner and the learning environment. Our main contribution is the detailed taxonomy that can be used to design and evaluate gamification design in learning environments

The effects of personalized gamification on students’ flow experience, motivation, and enjoyment

Gamification refers to the attempt to transform different kinds of systems to be able to better invoke positive experiences such as the flow state. However, the ability of such intervention to invoke flow state is commonly believed to depend on several moderating factors including the user’s traits. Currently, there is a dearth of research on the effect of user traits on the results of gamification. Gamer types (personality traits related to gaming styles and preferences) are considered some of the most relevant factors affecting the individual’s susceptibility to gamification. Therefore, in this study we investigate how gamer types from the BrainHex taxonomy (achiever, conqueror, daredevil, mastermind, seeker, socializer and survivor) moderate the effects of personalized/non-personalized gamification on users’ flow experience (challenge-skill balance, merging of action and awareness, clear goals, feedback, concentration, control, loss of self-consciousness and autotelic experience), enjoyment, perception of gamification and motivation. We conducted a mixed factorial within-subject experiment involving 121 elementary school students comparing a personalized version against a non-personalized version of a gamified education system. There were no main effects between personalization and students’ flow experience, perception of gamification and motivation, and enjoyment. Our results also indicate patterns of characteristics that can lead students to the high flow experience (e.g., those who prefer to play multiplayer have a high flow experience in both personalized and non-personalized versions). Based on our results, we provided recommendations to advance the design of gamifed educational systems.publishedVersionPeer reviewe