How should we measure online learning activity?

O’Riordan, Tim; Millard, David E.; Schulz, John

doi:10.3402/rlt.v24.30088

Cited by 20 publications

(8 citation statements)

References 35 publications

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“…The CoI, structure of observed learning outcomes and Bloom’s taxonomy are widely used models to study learning ecosystems (O’Riordan et al , 2016). The CoI model has especially seen wide acceptance for online learning systems.…”

Section: Literature Reviewmentioning

confidence: 99%

An empirical study on the online learning experience of MOOCs: Indian students’ perspective

Pillai¹

2019

IJEM

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Purpose The purpose of this paper is to investigate the online learning experience (LE) of massive open online courses (MOOCs) among the students in India using the lens of community of inquiry (CoI) model and two additional contextual factors. Design/methodology/approach The study conducted a survey using a structured questionnaire among the undergraduate and postgraduate students to examine the LE of MOOCs using the CoI framework and contextual variables – technical barrier (TB) and hedonic motivation (HD). The primary data were analyzed with the partial least squares structural equation modeling technique. Findings The results show that teaching presence (TP) influences cognitive presence (CP) and social presence (SP). SP influences CP. It is also found that TP, SP and CP influence the LE of MOOCs. It is found that TB negatively influences LE but is not significant and HD significantly influences LE positively for MOOCs. Research limitations/implications This study has a few limitations as it is a cross-sectional study in India, which surveyed undergraduate and postgraduate MOOCs learners, and caution needs to be taken while generalizing the outcomes. Further studies can be conducted across other countries considering demographic factors like age, gender, income groups, education and profession. Practical implications This research highlights the antecedents influencing the LE of MOOC learners using the CoI framework which will help the MOOC designers and marketers to apprehend the factors influencing LE. The results of this research will help them formulate suitable strategies in the design and delivery of MOOCs to improve the LE of learners. Originality/value This unique research investigates and empirically validates the CoI framework to understand LE of MOOC learners in India. This research extends the CoI framework by adding contextual factors – TB and HD in the context of a developing country.

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Section: Literature Reviewmentioning

confidence: 99%

An empirical study on the online learning experience of MOOCs: Indian students’ perspective

Pillai¹

2019

IJEM

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“…Future work on analysis of our engineering MOOC data should include more detailed analysis of comments e.g., conversation length [57], proportion of replies, length of messages, or textual analysis of the content of comments [30,58], which will allow us to understand whether a higher comment ratio relates to interaction, rather than simply multiple comment posting, and to evaluate social presence and its impact on completion rates and the educational experience more widely. A deeper textual analysis of comments would also enable us to understand more about the relative appeal of the three engineering sub-disciplines covered in the course.…”

Section: Conversation Length and Commenter Interactionmentioning

confidence: 99%

Establishing Social Learning in an Engineering MOOC: Benefits for Diversity and Inclusion in Engineering Education

Brereton

Young²

2022

Sustainability

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Recent Higher Education Statistics Agency data shows that only 20% of engineering students at UK Universities are female, despite the hard work being undertaken by many educational institutions to address this gender imbalance via outreach events and special interventions focussing on girls/women in STEM. It has been argued that student-centred teaching methods, together with changes in the engineering curriculum itself, which emphasise the social, creative, and human-centred aspects of the discipline, are required to effect real change in engaging with those from traditionally underrepresented groups. Through analysing quantitative data on age, gender, learner type, and commenting rates in peer-to-peer discussions, we examine the development and delivery of an engineering MOOC, before, during, and after COVID-19-related lockdowns in the UK, to identify what aspects of online learning might be harnessed to improve diversity in engineering education. The results show that the MOOC attracted a better gender balance than reported for UK-based in-person engineering programmes. In addition, we show that careful structuring of discussion prompts encouraged higher levels of social learning. We recommend the continued use of interactive and discursive elements within a blended learning environment to positively impact diversity and inclusion in engineering education specifically, and STEM education in general.

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“…In current online education, the pedagogical experiment known as Massive Open Online Courses (MOOCs) provides a useful lens for understanding how the learner connects to the content. Despite courses featuring world‐class scholars and instructors on varied subjects, all without any financial commitment, MOOCs still struggle with student participation, retention, and completion (Manathunga and Hernandez‐Leo 2015; O'Riordan, Millard, and Schulz 2016). Across the literature, the lessons are parallel for MOOCs and nonmassive online education: interactivity with the content, instructor, and classmates are all opportunities for productive engagement.…”

Section: The Relationships Of Online Teaching and Learningmentioning

confidence: 99%