Characterizing Comment Types and Levels of Engagement in Video-Based Learning as a Basis for Adaptive Nudging

Abstract

Video is frequently used as a learning medium in a variety of educational settings, including large online courses as well as informal learning scenarios. To foster learner engagement around instructional videos, our learning scenario facilitates interactive note taking and commenting similar to popular social video-sharing platforms. This approach has recently been enriched by introducing nudging mechanisms, which raises questions about ensuing learning effects. To better understand the nature of these effects, we take a closer look at the content of the comments. Our study is based on an ex post analysis of a larger data set from a recent study. As a first step of analysis, video comments are clustered based on a feature set that captures the temporal and semantic alignment of comments with the videos. Based on the ensuing typology of comments, learners are characterized through the types of comments that they have contributed. The results will allow for a better targeting of nudges to improve video-based learning.

A network analytic approach to integrating multiple quality measures for asynchronous online discussions

“…The students who contributed the most frequently tended to generate questions rather than building on what others had written. An intervention to encourage students to generate more content [30] simply increased the proportion of shallow and simple (Active mode) messages and did not improve learning gains.…”

“…The extended ICAP schema was used to label messages in MOOC discussion forums [31,32]. It was also used to classify student comments on an annotated electronic course text [36] and on MOOC videos [30], although in the latter case the activity was carried out individually with no scope for interaction between participants. Results from these studies indicated that interaction was rare and the majority of messages did not receive contentful responses.…”

“…The primary role of teaching presence is to support the development of cognitive presence [15,16], so it is important to evaluate the effect of different instructional scaffolds on the development of concepts from the two frameworks and the associations between them. It is easy to imagine how changes in knowledge construction prompted by an intervention could improve one metric, while leaving another unaffected or even reduced -for example, by increasing the quantity of simple questions asked [30]. In this study, we specifically focused on two types of intervention to examine whether and how they moderated the associations between CoI and ICAP.…”

Predicting and Explaining the Acceptance of Social Video Platforms for Learning: The Case of Brazilian YouTube Users

“…Notwithstanding the expected content redundancy and the problem of finding the right educational video [29], YouTube is the most recurrent social video tool used in education [26]. In addition, it is one of the first sources for learners when they want to learn something new [5], and it is capable of enhancing the learning experience considering that video is significant to the subject at hand [30]. Four lines of research can be identified in the literature regarding the use of the YouTube platform in education: educational video quality [29,31]; self-directed and long-life learning [21,32]; the cultural dimension [7]; and acceptance and use [15][16][17].…”

“…This behavior has allowed them, over time, to become platforms to gather information and help to learn [4]. In fact, today, YouTube is the first source for learners when they want to learn something new [5,6].…”