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Learning at distance: Effects of interaction traces on academic achievement

Joksimović Srećko, Gašević Dragan, Loughin Thomas M., Kovanović Vitomir, and Hatala Marek
Journal Paper Computers & Education, Volume 87, September 2015, Pages 204-217, ISSN 0360-1315, http://dx.doi.org/10.1016/j.compedu.2015.07.002.

Abstract

Contemporary literature on online and distance education almost unequivocally argues for the importance of interactions in online learning settings. Nevertheless, the relationship between different types of interactions and learning outcomes is rather complex. Analyzing 204 offerings of 29 courses, over the period of six years, this study aimed at expanding the current understanding of the nature of this relationship. Specifically, with the use of trace data about interactions and utilizing the multilevel linear mixed modeling techniques, the study examined whether frequency and duration of student–student, student–instructor, student–system, and student–content interactions had an effect of learning outcomes, measured as final course grades. The findings show that the time spent on student–system interactions had a consistent and positive effect on the learning outcome, while the quantity of student–content interactions was negatively associated with the final course grades. The study also showed the importance of the educational level and the context of individual courses for the interaction types supported. Our findings further confirmed the potential of the use of trace data and learning analytics for studying learning and teaching in online settings. However, further research should account for various qualitative aspects of the interactions used while learning, different pedagogical/media features, as well as for the course design and delivery conditions in order to better explain the association between interaction types and the learning achievement. Finally, the results might imply the need for the development of the institutional and program-level strategies for learning and teaching that would promote effective pedagogical approaches to designing and guiding interactions in online and distance learning settings.

Analytics of communities of inquiry: Effects of learning technology use on cognitive presence in asynchronous online discussions

Kovanović Vitomir, Gašević Dragan, Joksimović Srećko, Hatala Marek, and Adesope Olusola
Journal Paper The Internet and Higher Education, Volume 27, October 2015, Pages 74-89, ISSN 1096-7516, http://dx.doi.org/10.1016/j.iheduc.2015.06.002

Abstract

This paper describes a study that looked at the effects of different technology-use profiles on educational experience within communities of inquiry, and how they are related to the students' levels of cognitive presence in asynchronous online discussions. Through clustering of students (N = 81) in a graduate distance education engineering course, we identified six different profiles: 1) task-focused users, 2) content-focused no-users, 3) no-users, 4) highly intensive users, 5) content-focused intensive users, and 6) socially-focused intensive users. Identified profiles significantly differ in terms of their use of learning platform and their levels of cognitive presence, with large effect sizes of 0.54 and 0.19 multivariate η2, respectively. Given that several profiles are associated with higher levels of cognitive presence, our results suggest multiple ways for students to be successful within communities of inquiry. Our results also emphasize a need for a different instructional support and pedagogical interventions for different technology-use profiles.

Modeling Learners' Social Centrality and Performance through Language and Discourse

Dowell Nia, Skrypnyk Oleksandra, Joksimović Srećko, Graesser, Arthur C., Dawson Shane, Gašević Dragan, de Vries Pieter, Hennis Thieme, and Kovanović Vitomir
Conference PapersThe 8th International Conference on Educational Data Mining, EDM 2015, 26-29 June, 2015 UNED, Madrid, Spain

Abstract

There is an emerging trend in higher education for the adoption of massive open online courses (MOOCs). However, despite this interest in learning at scale, there has been limited work investigating the impact MOOCs can play on student learning. In this study, we adopt a novel approach, using language and discourse as a tool to explore its association with two established measures related to learning: traditional academic performance and social centrality. We demonstrate how characteristics of language diagnostically reveal the performance and social position of learners as they interact in a MOOC. We use CohMetrix, a theoretically grounded, computational linguistic modeling tool, to explore students’ forum postings across five potent discourse dimensions. Using a Social Network Analysis (SNA) methodology, we determine learners’ social centrality. Linear mixed-effect modeling is used for all other analyses to control for individual learner and text characteristics. The results indicate that learners performed significantly better when they engaged in more expository style discourse, with surface and deep level cohesive integration, abstract language, and simple syntactic structures. However, measures of social centrality revealed a different picture. Learners garnered a more significant and central position in their social network when they engaged with more narrative style discourse with less overlap between words and ideas, simpler syntactic structures and abstract words. Implications for further research and practice are discussed regarding the misalignment between these two learning-related outcomes.

Recognising learner autonomy: Lessons and reflections from a joint x/c MOOC

Dawson Shane, Joksimović Srećko, Kovanović Vitomir, Gašević Dragan, and Siemens George
Conference Papers38th HERDSA Annual International Conference, 6-9 July 2015, Melbourne, Australia (best paper award)

Abstract

Higher Education Institutions are increasingly called upon to provide more flexible student learning pathways – in degree programs as well as through the introduction of methods for micro-credentialing. However, the rhetoric of establishing such open and personalised learning pathways is far easier than the reality of implementation and organisational change. For instance, universities have long struggled to break away from the "credit hour" even while learners are being challenged to be more independent in their learning choices and education needs. The intent of this paper is to explore new models of education that embrace open learning pathways for lifelong learning and productive participation in the information age. The paper draws on the recent research and experiences gained from running a simultaneous xMOOC and cMOOC (a dual layer MOOC) using newly developed software based on the principles of student selfregulated learning. The software, ProSOLO, links a user’s nominated learning goals and experiences directly with their achievement of stated competencies. This process provides learners with greater autonomy in their study by removing the rigidity of more traditional education programs and offers new models of micro-credentialing.

The History and State of Online Learning

Joksimović Srećko, Kovanović Vitomir, Skrypnyk Oleksandra, Gašević Dragan, Dawson Shane, and Siemens George
ReportIn Siemens George, Gašević Dragan, and Dawson Shane - Preparing for the digital university: a review of the history and current state of distance, blended, and online learning, pages 93-132, 2015.

Abstract

Higher Education Institutions are increasingly called upon to provide more flexible student learning pathways – in degree programs as well as through the introduction of methods for micro-credentialing. However, the rhetoric of establishing such open and personalised learning pathways is far easier than the reality of implementation and organisational change. For instance, universities have long struggled to break away from the "credit hour" even while learners are being challenged to be more independent in their learning choices and education needs. The intent of this paper is to explore new models of education that embrace open learning pathways for lifelong learning and productive participation in the information age. The paper draws on the recent research and experiences gained from running a simultaneous xMOOC and cMOOC (a dual layer MOOC) using newly developed software based on the principles of student selfregulated learning. The software, ProSOLO, links a user’s nominated learning goals and experiences directly with their achievement of stated competencies. This process provides learners with greater autonomy in their study by removing the rigidity of more traditional education programs and offers new models of micro-credentialing.

Social presence in online discussions as a process predictor of academic performance

Joksimović Srećko, Gašević Dragan, Kovanović Vitomir, Riecke Bernhard E., and Hatala Marek
Journal Paper Journal of Computer Assisted Learning, 2015, http://dx.doi.org/10.1111/jcal.12107

Abstract

With the steady development of online education and online learning environments, possibilities to support social interactions between students have advanced significantly. This study examined the relationship between indicators of social presence and academic performance. Social presence is defined as students' ability to engage socially with an online learning community. The results of a multiple regression analysis showed that certain indicators of social presence were significant predictors of final grades in a master's level computer science online course. Moreover, the study also revealed that teaching presence moderated the association between social presence and academic performance, indicating that a course design that increased the level of meaningful interactions between students had a significant impact on the development of social presence, and thus could positively affect students' academic performance. This is especially important in situations when discussions are introduced to promote the development of learning outcomes assessed in courses. Another implication of our results is that indicators of social presence can be used for early detection of students at risk of failing a course. Findings inform research and practice in the emerging field of learning analytics by prompting the opportunities to offer actionable insights into the reasons why certain students are lagging behind.

Roles of course facilitators, learners, and technology in the flow of information of a cMOOC

Skrypnyk Oleksandra, Joksimović Srećko, Kovanović Vitomir, Gašević Dragan, and Dawson Shane
Journal PaperThe International Review of Research in Open and Distributed Learning, Volume 16, Number 3, June 2015. ISSN 1492-3831

Abstract

Distributed Massive Open Online Courses (MOOCs) are based on the premise that online learning occurs through a network of interconnected learners. The teachers’ role in distributed courses extends to forming such a network by facilitating communication that connects learners and their separate personal learning environments scattered around the Internet. The study reported in this paper examined who fulfilled such an influential role in a particular distributed MOOC – a connectivist course (cMOOC) offered in 2011. Social network analysis was conducted over a sociotechnical network of the Twitter-based course interactions, comprising both human course participants and hashtags; where the latter represented technological affordances for scaling course communication. The results of the week-by-week analysis of the network of interactions suggest that the teaching function becomes distributed among influential actors in the network. As the course progressed, both human and technological actors comprising the network subsumed the teaching functions, and exerted influence over the network formation. Regardless, the official course facilitators preserved a high level of influence over the flow of information in the investigated cMOOC.

What public media reveals about MOOCs: A systematic analysis of news reports

Kovanović Vitomir, Joksimović Srećko, Gašević Dragan, Siemens George, and Hatala Marek
Journal PaperBritish Journal of Educational Technology, Volume 46, Issue 3, pages 510–527, May 2015, DOI: 10.1111/bjet.12277.

Abstract

One of the striking differences between massive open online courses (MOOCs) and previous innovations in the education technology field is the unprecedented interest and involvement of the general public. As MOOCs address pressing problems in higher education and the broader educational practice, awareness of the general public debate around MOOCs is essential. Understanding the public discourse around MOOCs can provide insights into important social and public problems, thus enabling the MOOC research community to better focus their research endeavors. While there have been some reports looking at the state of the MOOC-related research, the analysis of the public debate surrounding MOOCs is still largely missing.

In this paper, we present the results of a study that looked at the content of the public discourse related to MOOCs. We identified the most important themes and topics in MOOC-related mainstream news reports. Our results indicate that coverage of MOOCs in public media is rapidly decreasing: by the middle of 2014, it decreased by almost 50% from the highest activity during 2013. In addition, the focus of those discussions is also changing. While the majority of discussions during 2012 and 2013 were focused on MOOC providers, the announcements of their partnerships, and million dollar investments, the current focus of MOOC discourse seems to be moving toward more productive topics focused on the overall position of MOOCs in the global educational landscape. Among different topics that this study discovered, government-related issues and the use of data and analytics are some of the topics that seem to be growing in popularity during the first half of 2014.

What do cMOOC participants talk about in social media?: A topic analysis of discourse in a cMOOC

Joksimović Srećko, Kovanović Vitomir, Jovanović Jelena, Zouaq Amal, Gašević Dragan, and Hatala Marek
Conference PapersIn Proceedings of the 5th International Conference on Learning Analytics and Knowledge(LAK 2015), Poughkeepsie, NY, USA, 16-20 March 2015

Abstract

Creating meaning from a wide variety of available information and being able to choose what to learn are highly relevant skills for learning in a connectivist setting. In this work, various approaches have been utilized to gain insights into learning processes occurring within a network of learners and understand the factors that shape learners' interests and the topics to which learners devote a significant attention. This study combines different methods to develop a scalable analytic approach for a comprehensive analysis of learners' discourse in a connectivist massive open online course (cMOOC). By linking techniques for semantic annotation and graph analysis with a qualitative analysis of learner-generated discourse, we examined how social media platforms (blogs, Twitter, and Facebook) and course recommendations influence content creation and topics discussed within a cMOOC. Our findings indicate that learners tend to focus on several prominent topics that emerge very quickly in the course. They maintain that focus, with some exceptions, throughout the course, regardless of readings suggested by the instructor. Moreover, the topics discussed across different social media differ, which can likely be attributed to the affordances of different media. Finally, our results indicate a relatively low level of cohesion in the topics discussed which might be an indicator of a diversity of the conceptual coverage discussed by the course participants.

How do you connect?: analysis of social capital accumulation in connectivist MOOCs

Joksimović Srećko, Dowell Nia, Skrypnyk Oleksandra, Kovanović Vitomir, Gašević Dragan, DawsonShane, and Graesser, Arthur C.
Conference PapersIn Proceedings of the 5th International Conference on Learning Analytics and Knowledge(LAK 2015), Poughkeepsie, NY, USA, 16-20 March 2015

Abstract

Connections established between learners via interactions are seen as fundamental for connectivist pedagogy. Connections can also be viewed as learning outcomes, i.e. learners' social capital accumulated through distributed learning environments. We applied linear mixed effects modeling to investigate whether the social capital accumulation interpreted through learners' centrality to course interaction networks, is influenced by the language learners use to express and communicate in two connectivist MOOCs. Interactions were distributed across the three social media, namely Twitter, blog and Facebook. Results showed that learners in a cMOOC connect easier with the individuals who use a more informal, narrative style, but still maintain a deeper cohesive structure to their communication.

Penetrating the black box of time-on-task estimation

Kovanović Vitomir, Gašević Dragan, Dawson Shane, Joksimović Srećko, Baker Ryan, and Hatala Marek
Conference PapersIn Proceedings of the 5th International Conference on Learning Analytics and Knowledge(LAK 2015), Poughkeepsie, NY, USA, 16-20 March 2015 (best paper award)

Abstract

All forms of learning take time. There is a large body of research suggesting that the amount of time spent on learning can improve the quality of learning, as represented by academic performance. The wide-spread adoption of learning technologies such as learning management systems (LMSs), has resulted in large amounts of data about student learning being readily accessible to educational researchers. One common use of this data is to measure time that students have spent on different learning tasks (i.e., time-on-task). Given that LMS systems typically only capture times when students executed various actions, time-on-task measures are estimated based on the recorded trace data. LMS trace data has been extensively used in many studies in the field of learning analytics, yet the problem of time-on-task estimation is rarely described in detail and the consequences that it entails are not fully examined.

This paper presents the results of a study that examined the effects of different time-on-task estimation methods on the results of commonly adopted analytical models. The primary goal of this paper is to raise awareness of the issue of accuracy and appropriateness surrounding time-estimation within the broader learning analytics community, and to initiate a debate about the challenges of this process. Furthermore, the paper provides an overview of time-on-task estimation methods in educational and related research fields.

Learning Analytics for Networked Learning Models

Joksimović Srećko, Gašević Dragan, and Hatala Marek
Journal Paper Journal of Learning Analytics, Special section: Sparks of the learning analytics future (LASI 2014), Volume 1, Number 3, 2014, p191-194, published online http://learning-analytics.info/

Abstract

Teaching and learning in networked setting has attained a significant amount of attention recently. The central topic of networked learning research is human-human and human-information interactions that occur within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach in analyzing their effects. Therefore, the main goal of this research is the development of a theoretical model that allows for a comprehensive and scalable analysis of how and why learners engage into collaboration in networked communities. The proposed research method, anticipated research outcomes and contributions to the learning analytics field are discussed.

Psychological characteristics in cognitive presence of communities of inquiry: A linguistic analysis of online discussions

Joksimović Srećko, Gašević Dragan, Kovanović Vitomir, Olusola Adescope, and Hatala Marek
Journal Paper The Internet and Higher Education, Volume 22, July 2014, p1-10, ISSN 1096-7516, published online http://dx.doi.org/10.1016/j.iheduc.2014.03.001

Abstract

Benefits of social interaction for learning have widely been recognized in ed-ucational research and practice. The existing body of research knowledge incomputer supported collaborative learning (CSCL) offers numerous practicalapproaches that can enhance educational experience in online group activities.The Community of Inquiry (CoI) model is one of the best-researched frameworksthat comprehensively explains different dimensions of online learning in commu-nities of inquiry. However, individual differences, well-established in educationalpsychology to affect learning (e.g., emotions, motivation and working memorycapacity), have received much less attention in the CSCL and CoI research pub-lished to date. This paper reports on the findings of a study that investigatedlinguistic features of online discussion transcripts coded by the four levels ofcognitive presence – a CoI dimension that explains the extent to which a com-munity can construct meaning from the initial practical inquiry to the eventualproblem resolution. The automated linguistic analysis, conducted by using theLinguistic Inquiry and Word Count (LIWC) framework, revealed that certainword categories – reported previously in the literature as accurate indicators ofspecific psychological characteristics – had distinct distributions for each levelof cognitive presence of the CoI framework. The most significant finding of thestudy is that linguistic proxies of increased cognitive load have unique repre-sentation patterns across the four levels of cognitive presence. Consequently,this study legitimizes more research on individual differences in general and oncognitive load theory in particular in communities of inquiry. The paper alsodiscusses implications for educational research, practice, and technology.

Where is research on massive open online courses headed? A data analysis of the MOOC Research Initiative

Gašević Dragan, Kovanović Vitomir, Joksimović Srećko, and Siemens George
Journal Paper The International Review of Research in Open and Distance Learning, Volume 15, Number 5, October 2014, p134-176, ISSN 1492-3831, published online http://www.irrodl.org/index.php/irrodl/article/view/1954

Abstract

This paper reports on the results of an analysis of the research proposals submitted to the MOOC Research Initiative (MRI) funded by the Gates Foundation and administered by Athabasca University. The goal of MRI was to mobilize researchers to engage into critical interrogation of MOOCs. The submissions – 266 in Phase 1, out of which 78 was recommended for resubmission in the extended form in Phase 2, and finally, 28 funded – were analyzed by applying conventional and automated content analysis methods as well as citation network analysis methods. The results revealed the main research themes that could form a framework of the future MOOC research: i) student engagement and learning success, ii) MOOC design and curriculum, iii) self-regulated learning and social learning, iv) social network analysis and networked learning, and v) motivation, attitude and success criteria. The theme of social learning received the greatest interest and had the highest success in attracting funding. The submissions that planned on using learning analytics methods were more successful. The use of mixed methods was by far the most popular. Design-based research methods were also suggested commonly, but the questions about their applicability arose regarding the feasibility to perform multiple iterations in the MOOC context and rather a limited focus on technological support for interventions. The submissions were dominated by the researchers from the field of education (75% of the accepted proposals). Not only was this a possible cause of a complete lack of success of the educational technology innovation theme, but it could be a worrying sign of the fragmentation in the research community and the need to increased efforts towards enhancing interdisciplinarity.

Externally-facilitated regulation scaffolding and role assignment to develop cognitive presence in asynchronous online discussions

Gašević Dragan, Kovanović Vitomir, Joksimović Srećko, and Siemens George
Journal Paper The Internet and Higher Education Volume 24, January 2015, Pages 53-65, ISSN 1096-7516, published online http://www.sciencedirect.com/science/article/pii/S1096751614000700

Abstract

This paper describes a study that looked at the effects of different teaching presence approaches in communities of inquiry, and ways in which student–student online discussions with high levels of cognitive presence can be designed. Specifically, this paper proposes that high-levels of cognitive presence can be facilitated in online courses, based on the community of inquiry model, by building upon existing research in i) self-regulated learning through externally-facilitated regulation scaffolding and ii) computer-supported collaborative learning through role assignment. We conducted a quasi-experimental study in a fully-online course (N = 82) using six offerings of the course. After performing a quantitative content analysis of online discussion transcripts, a multilevel linear modeling analysis showed the significant positive effects of both externally-facilitated regulation scaffolding and role assignment on the level of cognitive presence. Specifically, the results showed that externally-facilitated regulation scaffolding had a higher effect on cognitive presence than extrinsically induced motivation through grades. The results showed the effectiveness of role assignment to facilitate a high-level of cognitive presence. More importantly, the results showed a significant effect of the interaction between externally-facilitated regulation scaffolding and role assignment on cognitive presence. The paper concludes with a discussion of practical and theoretical implications.

Automated Cognitive Presence Detection in Online Discussion Transcripts

Kovanović Vitomir, Joksimović Srećko, Gašević Dragan, and Hatala Marek
Conference PapersIn Proceedings of the Learning Analytics & Machine Learning Workshop, held at the 4th International Conference on Learning Analytics and Knowledge (LAK 2014), Indianapolis, IN, USA, 24-28 March 2014, published online (4 pages) http://ceur-ws.org/Vol-1137/LA_machinelearning_submission_1.pdf

Abstract

In this paper we present the results of an exploratory study that examined the use of text mining and text classification for the automation of the content analysis of discussion transcripts within the context of distance education. We used Community of Inquiry (CoI) framework and focused on the content analysis of the cognitive presence construct given its central position within the CoI model. Our results demonstrate the potentials of proposed approach; The developed classifier achieved 58.4% accuracy and Cohen’s Kappa of 0.41 for the 5-category classification task. In this paper we analyze different classification features and describe the main problems and lessons learned from the development of such a system. Furthermore, we analyzed the use of several novel classification features that are based on the specifics of cognitive presence construct and our results indicate that some of them significantly improve classification accuracy.

What is the source of social capital? The association between social network position and social presence in communities of inquiry

Kovanović Vitomir, Joksimović Srećko, Gašević Dragan, and Hatala Marek
Conference PapersIn Proceedings of the 1st International Workshop on: Graph-Based Educational Datamining (G-EDM), held at the 7th International Conference on Educational Datamining, London, UK, 4-7 July 2014, p21-28, published online http://ceur-ws.org/Vol-1183/gedm2014_proceedings.pdf

Abstract

It is widely accepted that the social capital of students – developed through their participation in learning communities – has a significant impact on many aspects of the students’ learning outcomes, such as academic performance, persistence, retention, program satisfaction and sense of community. However, the underlying social processes that contribute to the development of social capital are not well understood. By using the well-known Community of Inquiry (CoI) model of distance and online education, we looked into the nature of the underlying social processes, and how they relate to the development of the students’ social capital. The results of our study indicate that the affective, cohesive and interactive facets of social presence significantly predict the network centrality measures commonly used for measurement of social capital.

Current state and future trends: a citation network analysis of the learning analytics field

Dawson Shane, Gaševic Dragan, Siemens George, and Joksimović Srećko
Conference PapersIn Proceedings of the 4th International Conference on Learning Analytics and Knowledge (LAK 2014), Indianapolis, IN, USA, 24-28 March 2014, p231-240 (nominated for the best paper award), doi:10.1145/2567574.2567585

Abstract

This paper provides an evaluation of the current state of the field of learning analytics through analysis of articles and citations occurring in the LAK conferences and identified special issue journals. The emerging field of learning analytics is at the intersection of numerous academic disciplines, and therefore draws on a diversity of methodologies, theories and underpinning scientific assumptions. Through citation analysis and structured mapping we aimed to identify the emergence of trends and disciplinary hierarchies that are influencing the development of the field to date. The results suggest that there is some fragmentation in the major disciplines (computer science and education) regarding conference and journal representation. The analyses also indicate that the commonly cited papers are of a more conceptual nature than empirical research reflecting the need for authors to define the learning analytics space. An evaluation of the current state of learning analytics provides numerous benefits for the development of the field, such as a guide for under-represented areas of research and to identify the disciplines that may require more strategic and targeted support and funding opportunities.

An empirical evaluation of ontology-based semantic annotators

Joksimović Srećko, Jovanović Jelena, Gašević Dragan, Zouaq Amal, and Jeremić Zoran
Conference PapersIn Proceedings of the 7th International Conference on Knowledge Capture (KCAP 2013), Banff, Canada, 23-26 June 2013, p109-112, doi:10.1145/2479832.2479855

Abstract

One of the most important prerequisites for achieving the Semantic Web vision is semantic annotation of data/resources. Semantic annotation enriches unstructured and/or semistructured content with a context that is further linked to the structured domain-specific knowledge. In particular, ontologybased semantic annotators enable the selection of a specific ontology to annotate content. This paper presents results of an empirical study of recent ontology-based annotators, namely Stanbol, KIM, and SDArch. Specifically, we evaluated the robustness of these annotators with respect to specific features of ontology concepts such as the length of concepts? labels and their linguistic categories (e.g., prepositions and conjunctions). Our results show that although significantly correlated according to most of the conducted evaluations, tools still exhibit their unique features that could be a topic of new research.

Applying ontology learning and graph measures to analyze learning analytics publications

Zouaq Amal, Joksimović Srećko, Gaševic Dragan
Conference PapersIn Proceedings of the 1st LAK Data Challenge, held at the 3rd International Conference on Learning Analytics and Knowledge (LAK 2013), Leuven, Belgium, 8-12 April 2013 (3rd Prize), published online (4 pages) http://ceur-ws.org/Vol-974/lakdatachallenge2013_08.pdf.

Abstract

In this paper, we show how ontology learning tools can be used to reveal (i) the central research topics that are tackled in the published literature on learning analytics and educational data mining; and (ii)relationships between these research topics and iii) (dis)similarities between learning analytics and educational data mining.