We used the ACM Digital Library and Google Scholar to search for suitable literature. The „snowball system“ was also used, but only for one or two papers. We expect to use this system, in which you search for relevant literature with the references made by papers about the topic, more after we have a clearer overview over our specific research question.

Some of the search terms that were used for the two academic search engines mentioned above were:

• online video learning
• remote learning
• online video learning interaction
• online lecture engagement
• online learning interaction

Since we were still a bit unsure about our specific research question (and if we should compare across all three of our suggested interaction classes: asynchronous, semi-synchronous and synchronous), research was gathered for all three of these groups alongside general research about interaction in online courses. The papers were then separated into four different classes:

• 1 General papers on online learning
• 2 Papers on asynchronous interaction (pre-recorded videos, no direct interaction)
• 3 Papers on semi-synchronous interaction (livestreams, interactions but with a slight and possible delay, mostly in text)
• 4 Papers on synchronous interaction (online classrooms, online conferences, direct interaction with instructors/lecturers over voice and/or video)

Papers about comparisons between these forms of interactions were not present or easily visible, which suggests that this is an interesting and not heavily researched topic that is worth looking into. Interactions were mostly constrained to one form of online lecture, either by video or by online classrooms (although a more specific search about live-streaming might give more results).

Research suggests that there are generally multiple forms of interaction that occur in online learning:

• Interaction between students and instructors/lecturers
• Interaction between students and students
• Interaction between students and content

As far as our research is concerned, we mainly want to investigate the interaction possibilities that the different forms of content delivery by lecturers offer. All three of these interactions can be present for asynchronous, semi-synchronous and synchronous interaction and we might want to look at one of these aspects in more detail depending on our specific research question.

The biggest amount of the research we gathered so far was about asynchronous interaction with learning videos. Some of the topics contained investigations on student behavior while watching the videos or how learning videos should be designed. Massive Open Online Courses (MOOC) were mentioned and researched a few times. A few of our papers were about live-streaming and only one paper was found that could be classified as synchronous interaction (although there was one that could be both about asynchronous and synchronous interaction). This is definitely one of the forms of interaction where additional research has to be gathered and searched for specifically, since the previous search strategies were still fairly broad.

The discussion with the group advisor is definitely a helpful next step to determine how much additional research needs to be gathered. A specific search for interaction with live-stream and online conferences or digital classrooms is still necessary since the general search did not provide a lot of research directly in that area.

Knapp, N. F. (2018). Increasing interaction in a flipped online classroom through video conferencing. TechTrends, 62(6), 618-624.

Kutnick, D. G., & Joyner, D. A. (2019, June). Synchronous at Scale: Investigation and Implementation of a Semi-Synchronous Online Lecture Platform. In Proceedings of the Sixth (2019) ACM Conference on Learning@ Scale (pp. 1-4).

Blaine, A. M. (2019). Interaction and presence in the virtual classroom: An analysis of the perceptions of students and teachers in online and blended Advanced Placement courses. Computers & Education, 132, 31-43.

He, W. (2013). Examining students’ online interaction in a live video streaming environment using data mining and text mining. Computers in Human Behavior, 29(1), 90-102.

Gajos, K. Z., Kim, J., Li, S. W., Cai, C. J., & Miller, R. C. (2014). Leveraging video interaction data and content analysis to improve video learning. Proceedings of the CHI2014 Learning Innovation at Scale Workshop.

Kim, J., Guo, P. J., Seaton, D. T., Mitros, P., Gajos, K. Z., & Miller, R. C. (2014, March). Understanding in-video dropouts and interaction peaks inonline lecture videos. In Proceedings of the first ACM conference on Learning@ scale conference (pp. 31-40).