Your click decides your fate: Leveraging clickstream patterns in MOOC videos to infer students' information processing and attrition behavior.

Published on Jul 26, 2014in arXiv: Human-Computer Interaction
Tanmay Sinha12
Estimated H-index: 12
,
Patrick Jermann24
Estimated H-index: 24
+ 1 AuthorsPierre Dillenbourg64
Estimated H-index: 64
Sources
Abstract
With an expansive and ubiquitously available gold mine of educational data, Massive Open Online courses (MOOCs) have become the an important foci of learning analytics research. The hope is that this new surge of development will bring the vision of equitable access to lifelong learning opportunities within practical reach. MOOCs offer many valuable learning experiences to students, from video lectures, readings, assignments and exams, to opportunities to connect and collaborate with others through threaded discussion forums and other Web 2.0 technologies. Nevertheless, despite all this potential, MOOCs have so far failed to produce evidence that this potential is being realized in the current instantiation of MOOCs. In this work, we primarily explore video lecture interaction in Massive Open Online Courses (MOOCs), which is central to student learning experience on these educational platforms. As a research contribution, we operationalize video lecture clickstreams of students into behavioral actions, and construct a quantitative information processing index, that can aid instructors to better understand MOOC hurdles and reason about unsatisfactory learning outcomes. Our results illuminate the effectiveness of developing such a metric inspired by cognitive psychology, towards answering critical questions regarding students' engagement, their future click interactions and participation trajectories that lead to in-video dropouts. We leverage recurring click behaviors to differentiate distinct video watching profiles for students in MOOCs. Additionally, we discuss about prediction of complete course dropouts, incorporating diverse perspectives from statistics and machine learning, to offer a more nuanced view into how the second generation of MOOCs be benefited, if course instructors were to better comprehend factors that lead to student attrition.
Figures & Tables
Download
đź“– Papers frequently viewed together
2014
6 Authors (Juho Kim, ..., Robert C. Miller)
2019
References13
Newest
Apr 7, 2014 in WWW (The Web Conference)
#1Ilona Nawrot (UNICAEN: University of Caen Lower Normandy)H-Index: 2
#2Antoine Doucet (UNICAEN: University of Caen Lower Normandy)H-Index: 19
The main objectives of massive open online courses (MOOC) are to foster knowledge through free high quality learning materials procurement; to create new knowledge through diverse users' interactions with the providing platform; and to empower research on learning. However, MOOC providers are also businesses (either profit or not-for-profit). They are still in the early stages of their development, but sooner or later, in order to secure their existence and assure their longterm growth, they wil...
Source
#1Philip J. Guo (UR: University of Rochester)H-Index: 33
#2Katharina Reinecke (UM: University of Michigan)H-Index: 21
The current generation of Massive Open Online Courses (MOOCs) attract a diverse student audience from all age groups and over 196 countries around the world. Researchers, educators, and the general public have recently become interested in how the learning experience in MOOCs differs from that in traditional courses. A major component of the learning experience is how students navigate through course content. This paper presents an empirical study of how students navigate through MOOCs, and is, ...
Source
#1Chinmay Kulkarni (Stanford University)H-Index: 16
#2Richard Socher (Stanford University)H-Index: 71
Last. Scott R. Klemmer (UCSD: University of California, San Diego)H-Index: 42
view all 4 authors...
Peer assessment helps students reflect and exposes them to different ideas. It scales assessment and allows large online classes to use open-ended assignments. However, it requires students to spend significant time grading. How can we lower this grading burden while maintaining quality? This paper integrates peer and machine grading to preserve the robustness of peer assessment and lower grading burden. In the identify-verify pattern, a grading algorithm first predicts a student grade and estim...
Source
With an expansive and ubiquitously available gold mine of educational data, Massive Open Online courses (MOOCs) have become the an important foci of learning analytics research. In this paper, we investigate potential reasons as to why are these digitalized learning repositories being plagued with huge attrition rates. We analyze an ongoing online course offered in Coursera using a social network perspective, with an objective to identify students who are actively participating in course discuss...
#1Krzysztof Z. Gajos (Harvard University)H-Index: 43
#2Juho KimH-Index: 18
Last. Robert C. MillerH-Index: 64
view all 5 authors...
Video has emerged as a dominant medium for online education, as witnessed by millions of students learning from educational videos on Massive Open Online Courses (MOOCs), Khan Academy, and YouTube. The large-scale data collected from students’ interactions with video provide a unique opportunity to analyze and improve the video learning experience. We combine click-level interaction data, such as pausing, resuming, or navigating between points in the video, and video content analysis, such as vi...
Source
May 18, 2013 in ICSE (International Conference on Software Engineering)
#1Nikolai Tillmann (Microsoft)H-Index: 41
#2Jonathan de Halleux (Microsoft)H-Index: 24
Last. Judith Bishop (Microsoft)H-Index: 17
view all 5 authors...
Massive Open Online Courses (MOOCs) have recently gained high popularity among various universities and even in global societies. A critical factor for their success in teaching and learning effectiveness is assignment grading. Traditional ways of assignment grading are not scalable and do not give timely or interactive feedback to students. To address these issues, we present an interactive-gaming-based teaching and learning platform called Pex4Fun. Pex4Fun is a browser-based teaching and learn...
Source
#1Alexander McAuleyH-Index: 2
#2Bonnie StewartH-Index: 8
Last. Dave CormierH-Index: 7
view all 4 authors...
#1Robert M. Carini (University of Louisville)H-Index: 15
#2George D. KuhH-Index: 82
Last. Stephen P. Klein (AN: RAND Corporation)H-Index: 24
view all 3 authors...
This study examines (1) the extent to which student engagement is associated with experimental and traditional measures of academic performance, (2) whether the relationships between engagement and academic performance are conditional, and (3) whether institutions differ in terms of their ability to convert student engagement into academic performance. The sample consisted of 1058 students at 14 four-year colleges and universities that completed several instruments during 2002. Many measures of ...
Source
#1Annie Lang (IU: Indiana University)H-Index: 53
This paper presents an information-processing model that is directly applicable to the investigation of how mediated messages are processed. It applies the model to the case of television viewing to demonstrate its applicability. It provides a measure for each part of the model. It presents evidence that supports the model in the television-viewing situation. Finally, it demonstrates how the model may be used to further research and understanding in well-known theoretical traditions. This model ...
Source
Cited By19
Newest
#1Simran SetiaH-Index: 2
Last. Neeru DubeyH-Index: 3
view all 5 authors...
Source
#1Namrata Srivastava (University of Melbourne)H-Index: 4
#2Sadia Nawaz (University of Melbourne)H-Index: 4
Last. James Bailey (University of Melbourne)H-Index: 48
view all 8 authors...
Video has become an essential medium for learning. However, there are challenges when using traditional methods to measure how learners attend to lecture videos in video learning analytics, such as difficulty in capturing learners’ attention at a fine-grained level. Therefore, in this paper, we propose a gaze-based metric—“with-me-ness direction” that can measure how learners’ gaze-direction changes when they listen to the instructor’s dialogues in a video-lecture. We analyze the gaze data of 45...
Source
#1Byungsoo Jeon (CMU: Carnegie Mellon University)H-Index: 5
#2Namyong Park (CMU: Carnegie Mellon University)H-Index: 9
This paper addresses a key challenge in MOOC dropout prediction, namely to build meaningful representations from clickstream data. While a variety of feature extraction techniques have been explored extensively for such purposes, to our knowledge, no prior works have explored modeling of educational content (e.g. video) and their correlation with the learner's behavior (e.g. clickstream) in this context. We bridge this gap by devising a method to learn representation for videos and the correlati...
#1Byungsoo Jeon (CMU: Carnegie Mellon University)H-Index: 5
#2Namyong Park (CMU: Carnegie Mellon University)H-Index: 9
Last. Seojin Bang (CMU: Carnegie Mellon University)H-Index: 4
view all 3 authors...
Massive Open Online Courses (MOOCs) have become popular platforms for online learning. While MOOCs enable students to study at their own pace, this flexibility makes it easy for students to drop out of class. In this paper, our goal is to predict if a learner is going to drop out within the next week, given clickstream data for the current week. To this end, we present a multi-layer representation learning solution based on branch and bound (BB) algorithm, which learns from low-level clickstream...
#1Malte Persike (University of Mainz)H-Index: 14
Lernvideos zahlen zu den wichtigsten digitalen Medien in der Hochschullehre. Kein anderes multimediales Format ist so unkompliziert herzustellen und zu publizieren wie das Lernvideo. Uberdies ist keines so gut wissenschaftlich untersucht. Dieses Kapitel nimmt zunachst eine Begriffsbestimmung der verschiedenen Videoformate fur die Lehre vor, beginnend bei der Vorlesungsaufzeichnung bis zum 360° Virtual Reality Video. Anschliesend wird der typische Produktionsprozess eines Lernvideos beschrieben, ...
Source
With the rise of social networking and the awareness of privacy protection, the large-scale positioning data is getting harder to access while the clickstream data of social networking is accumulating. It is necessary to conduct a comprehensive study on the temporal property and spatial distribution of social network’s clickstream to determine the latent relationship between clickstream and location semantics which semantically annotate locations to help us understand the purpose of a social net...
Source
#1Byungsoo Jeon (CMU: Carnegie Mellon University)H-Index: 5
#2Eyal Shafran (Western Governors University)H-Index: 1
Last. Carolyn Penstein Rosé (CMU: Carnegie Mellon University)H-Index: 54
view all 5 authors...
This paper addresses a key challenge in Educational Data Mining, namely to model student behavioral trajectories in order to provide a means for identifying students most at-risk, with the goal of providing supportive interventions. While many forms of data including clickstream data or data from sensors have been used extensively in time series models for such purposes, in this paper we explore the use of textual data, which is sometimes available in the records of students at large, online uni...
#1Graham Pike (OU: Open University)H-Index: 10
#2Hannah Gore (OU: Open University)H-Index: 2
Since their inception in 2012, the most significant challenge faced in the production and presentation of Massive Open Online Courses (MOOCs) has been how to engage and retain learners. Although often heralded as the next step in the evolution of online education, even if MOOCs represent a revolution in terms of the number of learners signing-up, they leave a lot to be desired with respect to the number of people who actually complete a course. This chapter explores some of the issues involved i...
Source
#1Juan Miguel L. Andres (UPenn: University of Pennsylvania)H-Index: 5
Research on learner behaviors and course completion within Massive Open Online Courses (MOOCs) has been mostly confined to single courses, making the findings difficult to generalize across different data sets and to assess which contexts and types of courses these findings apply to. This paper reports on the development of the MOOC Replication Framework (MORF), a framework that facilitates the replication of previously published findings across multiple data sets and the seamless integration of...
Source
#1Liang Yi Li (NCU: National Central University)H-Index: 1
Abstract Accessing learning materials, that is, lecture slides, video lectures, shared assignments, and forum messages, is the most frequently performed online learning activity. However, students with different purposes, motivations, and preferences may exhibit different behaviors when accessing these materials. These different behaviors may further affect their learning performance. This study analyzed system logs recorded by a Learning Management System in which 59 computer science students p...
Source
This website uses cookies.
We use cookies to improve your online experience. By continuing to use our website we assume you agree to the placement of these cookies.
To learn more, you can find in our Privacy Policy.