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Research output: Thesis › Doctoral Thesis
Research output: Thesis › Doctoral Thesis
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TY - BOOK
T1 - The Role of Connectors in Supporting Knowledge Construction in xMOOC Learning Networks
T2 - A Mixed Methods Case Study
AU - McMinn, Sean
PY - 2021
Y1 - 2021
N2 - Massive Open Online Courses (MOOCs) are a relatively new phenomenon in the field of online education. The literature has both praised the potential for xMOOCs, highly structured courses that centre around a series of short video lectures, automated marking, and peer evaluation, enhancing learning outcomes and condemned them for not being innovative at all, with some suggesting that xMOOCs reinforce a teacher-centred approach to teaching and learning. Empirical research on xMOOCs is still relatively new, ranging from the subject of attrition rates, communication patterns, , and learning analytics. Yet, there is still little empirical evidence showing how learning occurs in xMOOCs. More specifically, it’s not understood how participants engage in collaborative dialogue and knowledge construction. Furthermore, the literature is lacking in describing how or who influences the sequence of knowledge construction in xMOOCs. Recent research suggests that a social network analysis approach to MOOC research may provide insight on how participants engage with each other, and whether some are more influential than others in how knowledge is shared, understood or constructed. This thesis adopts a mixed methods case study design using (1) social network analysis, and (2) Interaction Analysis Model (IAM) to explore how xMOOC participants with high centrality measures support knowledge construction. The results show that SNA of xMOOC discussion forums can identify participants who are in the position to be connectors, highly influential in a social network; however, IAM of the discussion forums suggest that they play a minimal role in the sequence of knowledge construction among participants. This suggests connectors are not influential in an xMOOC learning network, despite the power of their position. The implications of these findings informs both researchers of how engagement and knowledge construction does not happen automatically, and that instructor or instructional design intervention may be needed.
AB - Massive Open Online Courses (MOOCs) are a relatively new phenomenon in the field of online education. The literature has both praised the potential for xMOOCs, highly structured courses that centre around a series of short video lectures, automated marking, and peer evaluation, enhancing learning outcomes and condemned them for not being innovative at all, with some suggesting that xMOOCs reinforce a teacher-centred approach to teaching and learning. Empirical research on xMOOCs is still relatively new, ranging from the subject of attrition rates, communication patterns, , and learning analytics. Yet, there is still little empirical evidence showing how learning occurs in xMOOCs. More specifically, it’s not understood how participants engage in collaborative dialogue and knowledge construction. Furthermore, the literature is lacking in describing how or who influences the sequence of knowledge construction in xMOOCs. Recent research suggests that a social network analysis approach to MOOC research may provide insight on how participants engage with each other, and whether some are more influential than others in how knowledge is shared, understood or constructed. This thesis adopts a mixed methods case study design using (1) social network analysis, and (2) Interaction Analysis Model (IAM) to explore how xMOOC participants with high centrality measures support knowledge construction. The results show that SNA of xMOOC discussion forums can identify participants who are in the position to be connectors, highly influential in a social network; however, IAM of the discussion forums suggest that they play a minimal role in the sequence of knowledge construction among participants. This suggests connectors are not influential in an xMOOC learning network, despite the power of their position. The implications of these findings informs both researchers of how engagement and knowledge construction does not happen automatically, and that instructor or instructional design intervention may be needed.
KW - MOOCs
KW - cMOOCs
KW - Knowledge Construction
KW - Connectors
KW - Social Network Analysis
KW - learning networks
KW - xMOOCs
U2 - 10.17635/lancaster/thesis/1264
DO - 10.17635/lancaster/thesis/1264
M3 - Doctoral Thesis
PB - Lancaster University
ER -