Interactive videos promote learner engagement by transforming the passive activity of watching videos into an active learning process. LIVE, a web platform developed in previous research that allows for the integration of interactive elements into videos, also supports embedding programming tasks. However, at the beginning of our research, the output of the submitted solution was automatically compared to the reference output, but the code itself still had to be checked manually, as no automatic process was available to verify the solution and provide feedback. To address this, a stand-alone application was developed that automatically evaluates students’ solutions to Python programming tasks using a self-hosted large language model. This application was then integrated into the existing platform. To test this approach, a massive open online course containing four interactive videos with several programming tasks and quizzes was created. Students’ performance was analyzed using quiz results, task submissions, self-assessments, and user statistics provided by the course platform and LIVE. The results indicate that utilizing a large language model for automated feedback can positively impact learning outcomes. However, some limitations must be taken into account, such as the need to correct some of the model’s generated outputs manually due to insufficient feedback quality for certain tasks. This suggests that the combination of automated and manual evaluation seems to be the most effective approach for now.
The importance of digital technologies, especially videos, increased over the course of the last few years. Whether they are used to watching the latest news or for entertainment purposes, one could say they have become almost omnipresent in everyday’s life. This development has also influenced education. Therefore, we want to examine the effects of interactive overlays such as programming tasks in interactive learning videos. For this purpose, a MOOC course was created to gain information about participants` learning success. To evaluate whether the interactive elements have a positive effect, two test groups completed the course. The results revealed that the test group with overlays performed better on average than the group without. Some limitations had to be considered, such as the smaller peer group that watched the videos without interactive elements.
Digital learning technologies are becoming increasingly important for our modern educational system. In addition to teaching methods that incorporate interactivity, these approaches benefit students’ overall learning experience and success by enhancing their attention and fostering a positive attitude towards the learning content being presented. Interactivity comes in various forms, and while a combination of distinct activities is beneficial, some are more effective at engaging students. Using digital technologies in an educational environment opens up new possibilities for students, teachers, and researchers. It provides new insights into learning behavior and enables the collection of interaction information. This data could, for example, show how often a video was paused or at what point students lost interest and left, but gaining such knowledge requires further processing. The use of visualizations that depict behavior, such as the change of attention over time, can be an effective way to present extracted information. Therefore, our research focuses on developing an application that enables us to generate various visualizations from the collected data. A single command-line input will be sufficient to create them. Furthermore, a video course was created from which we collected behavioral data. Our results aim to showcase the benefits of interactivity, and that the created figures can be used for data evaluation verifies the versatility of the generated visualizations.
Massive Open Online Courses (MOOCs) gewinnen immer mehr an Stellenwert in der Bildung. Eines der wichtigsten Techniken zur Vermittlung der Inhalte in einem MOOC ist das Video. Videos sind allerdings ein passives Medium und die Teilnehmer:innen verlieren schnell an Aufmerksamkeit. Eine Möglichkeit diesem Problem entgegenzuwirken, sind interaktive Elemente die in das Video eingebettet werden. Im Rahmen dieses Beitrags wird anhand von zwei MOOCs auf iMooX.at gezeigt, wie mit einer speziellen Videoplattform interaktive Elemente eingebettet werden können und welche Auswirkungen das auf die Aufmerksamkeit und den Lernerfolg der Teilnehmer:innen hat. Da es bei diesen MOOCs um die Grundlagen der Programmierung mit Python geht, wurden vor allem interaktive Programmieraufgaben in die Videos eingebettet. In einer ausführlichen Analyse konnte gezeigt werden, dass die Performance der Teilnehmer:innen durch den Einsatz dieser interaktiven Aufgaben gestiegen ist.
Due to the fact that students’ attention is the most crucial resource in a high-quality course it is from high importance to control and analyze it. This could be done by using the interaction and the communication because they are known as valuable influencing factors of the attention. In this publication we introduce a web-based information system which implements an attention-profiling algorithm for learning-videos as well as live-broadcastings of lectures. For that different methods of interaction are offered and analyzed. The evaluation points out that the attention profiling algorithm delivers realistic values.