Refining qualitative ethnographies using Epistemic Network Analysis: A study of socioemotional learning dimensions in a Humanistic Knowledge Building Community

Hod, Yotam; Katz, Shir; Eagan, Brendan

doi:10.1016/j.compedu.2020.103943

Cited by 21 publications

(8 citation statements)

References 21 publications

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“…ENA is an important method to quantitatively encode text data generated during learners' interactions with the help of cognitive framework theory and to characterize and analyse the network relationships among learners' cognitive elements using dynamic network models (Shaffer et al, 2016). Currently, in online learning contexts, ENA is not only applied to analyse changes and differences in learners' cognitive development (Wu et al, 2020) but also widely used to analyse the evolution of sentiments (Hod et al, 2020) and the development of collaborative problem‐solving skills (Zhang et al, 2022). Because ENA can quantify and characterize both the structure and strength of the connections between elements in the network, as well as the changes in the structure and strength of the connections that occur over time.…”

Section: Literature Reviewmentioning

confidence: 99%

Understanding the evolution of cognitive engagement with interaction levels in online learning environments: Insights from learning analytics and epistemic network analysis

Guo

Zheng

2023

Computer Assisted Learning

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Background: There is a strong association between interactions and cognitive engagement, which is crucial for constructing new cognition and knowledge.Although interactions and cognitive engagement have attracted extensive attention in online learning environments, few studies have revealed the evolution of cognitive engagement with interaction levels.Objectives: The study aims to automatically identify learners' interactions and cognitive engagement and then analyse the evolution of learners' cognitive engagement with interaction levels and during different stages of online learning. Methods:The participants of the study were learners who participated in an online open course. Their text data from discussion forums on five learning themes were collected. Data were analysed using text mining and ENA.Results: Learners' cognitive engagement in online learning was related to interaction levels. As learners' online interaction levels changed from surface to deep, cognitive engagement levels changed from low to high. With the continuous occurrence of deep interactions, cognitive feedback became more complex. At the social-emotional interaction level, although learners' cognitive engagement levels began to change from low to high, complex cognitive feedback was still insufficient. In addition, the analysis of the evolution of cognitive engagement during different stages of online learning showed that learners' patterns of cognitive engagement changed significantly as the learning process continued, from initially dynamic and complex to a stable development pattern. Implications:The results of the study are of theoretical significance and practical guidance for further understanding the relationship between online interaction levels and cognitive engagement as well as the process of online collaborative knowledge exploration, construction, and even connectivity.

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Section: Literature Reviewmentioning

confidence: 99%

Understanding the evolution of cognitive engagement with interaction levels in online learning environments: Insights from learning analytics and epistemic network analysis

Guo

Zheng

2023

Computer Assisted Learning

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“…The coded data were extracted from a diverse range of sources, for example, online discussions, interviews, learner interactions, surveys, log files, and other miscellaneous forms (Figure 4). Online discussions were the source in 18 studies (23.7%), in which researchers explored, for example, virtual internship discussions [26], [46]- [50] , online discourse [15], [18], [51]- [54] or community of inquiry [23], [55]- [59].…”

Section: Raw Data Formmentioning

confidence: 99%

“…The deductive coding was used in 32 (42.1%) articles with a top-down approach based on codes derived from previous research. Another 25 (32.9%) articles used inductive coding in a bottom-up approach that was generated from the data with no predefined coding framework using, for example, the grounded theory approach [21], [25], [45], [49], [51], [54], [60], [61], [64], [68], [69], [101], [102]. The third type of coding, which was reported in 19 articles (25%), used a combination of coding methods.…”

Section: Comparisonsmentioning

confidence: 99%

A Systematic Literature Review of Empirical Research on Epistemic Network Analysis in Education

et al. 2022

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“…The study had two aims. Firstly, it aimed to understand what may be needed in teacher training programs to enable pre-service teacher students to “become more intentional in their activities” (Hod et al. , 2020, p. 12).…”

Section: The “Impacts and Implications” Studymentioning

confidence: 99%

The SAMR model as a framework for scaffolding online chat: a theoretical discussion of the SAMR model as a research method during these “interesting” times

Arantes

2022

QRJ

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PurposeThe purpose of this paper is to explore the potential of the substitution, augmentation, modification and redefinition (SAMR) model as a research method via a project that aimed to investigate pre-service teachers' negotiation of data-rich environments.Design/methodology/approachThe project that underpins this paper saw the author working with a group of seven pre-service teachers through an online learning community on WhatsApp to explore their understanding of increasingly complex computational topics associated with the “Implications and Impacts” component of the digital technologies curriculum.FindingsThe knowledge and experiences of the pre-service teachers suggest considerable unexplored potential through the alignment of the SAMR model in online learning communities.Originality/valueThe paper draws attention to a range of opportunities associated with prompting discussion about increasingly complex topics in online learning communities. The adoption of the SAMR model offers a framework in education and the social sciences. It stresses the affordances enabled due to the personalized, ubiquitous and situated nature of the method. Unique contributions include the interpretive and critical approaches discussed in terms of research methods. The paper may be of value to researchers who are interested in a scaffolded means to engage with participants through an online learning community.

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Refining qualitative ethnographies using Epistemic Network Analysis: A study of socioemotional learning dimensions in a Humanistic Knowledge Building Community

Cited by 21 publications

References 21 publications

Understanding the evolution of cognitive engagement with interaction levels in online learning environments: Insights from learning analytics and epistemic network analysis

Understanding the evolution of cognitive engagement with interaction levels in online learning environments: Insights from learning analytics and epistemic network analysis

A Systematic Literature Review of Empirical Research on Epistemic Network Analysis in Education

The SAMR model as a framework for scaffolding online chat: a theoretical discussion of the SAMR model as a research method during these “interesting” times

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