Ordered Network Analysis

Tan, Yuanru; Ruis, Andrew R.; Marquart, Cody; Cai, Zhiqiang; Knowles, Mariah A.; Shaffer, David Williamson

doi:10.1007/978-3-031-31726-2_8

Cited by 15 publications

(4 citation statements)

References 15 publications

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“…We applied ordered network analysis to our faculty response data using the ONA Web Tool (version 1.7.0) [43,44]. Our units were divided into two groups: the faculty and the research team, and we analyzed the conversation using a moving stanza window of four lines.…”

Section: Faculty Responsesmentioning

confidence: 99%

Rethinking Undergraduate Computer Science Education: Using the 4Es Heuristic to Center Students in an Introductory Computer Science Course

Starks,

Reeves,

Rickert

et al. 2024

Education Sciences

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There is a nationwide effort to increase the representation and engagement of minoritized students in computer science education. Discourse about the barriers to diversity among computer science majors is often characterized by student pathologies and does not consider the impacts of classroom culture and instructor pedagogies. Amid the push for strategies to recruit and retain minoritized students in computer science, little has been done to transform curriculum and analyze faculty perspectives on curriculum and pedagogy as methods to increase students’ access to the computer science major. This paper presents an example of curriculum redesign for an undergraduate introductory computer science course (ICS) that sought to address issues of inequitable representation by centering student identities and redistributing power in favor of students. The authors draw upon critical sociocultural and the 4Es heuristic for disciplinary literacy to reimagine the ICS course as a space that centers on the important roles of identity and power in solving for diversity in computer science education. We highlight for researchers and practitioners how our work may be used to disrupt meritocratic practices that alienate minoritized and economically disadvantaged students and to expand definitions of mastery and expertise in computer science education.

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Section: Faculty Responsesmentioning

confidence: 99%

Rethinking Undergraduate Computer Science Education: Using the 4Es Heuristic to Center Students in an Introductory Computer Science Course

Starks,

Reeves,

Rickert

et al. 2024

Education Sciences

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“…A detailed technical description of ONA is beyond the scope of this study. For more information, see the study by Tan et al (2023), which describes ONA, as well as the study by Shaffer et al (2016), which describes epistemic network analysis (ENA), the widely used learning analytic technique on which ONA is based. Briefly, ONA builds on ENA to measure and visualize the frequency of transitions between coded events in the data.…”

Section: Data Analysismentioning

confidence: 99%

“…Moreover, previous studies have acknowledged that SRL processes are context-sensitive and sequence-specific—that is, any given SRL process can precede or follow other SRL processes, and different orders imply different meanings (Fan et al, 2023 ). To account for the connected and sequential nature of SRL processes, we used the network analytic technique, ordered network analysis (ONA) (Tan et al, 2023 ). This technique, as well as the details of our experimental design and data, is described in the sections below.…”

Section: Introductionmentioning

confidence: 99%

Analytics of self-regulated learning scaffolding: effects on learning processes

Fan

Tan

et al. 2023

Front. Psychol.

Self Cite

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Self-regulated learning (SRL) is the ability to regulate cognitive, metacognitive, motivational, and emotional states while learning and is posited to be a strong predictor of academic success. It is therefore important to provide learners with effective instructions to promote more meaningful and effective SRL processes. One way to implement SRL instructions is through providing real-time SRL scaffolding while learners engage with a task. However, previous studies have tended to focus on fixed scaffolding rather than adaptive scaffolding that is tailored to student actions. Studies that have investigated adaptive scaffolding have not adequately distinguished between the effects of adaptive and fixed scaffolding compared to a control condition. Moreover, previous studies have tended to investigate the effects of scaffolding at the task level rather than shorter time segments—obscuring the impact of individual scaffolds on SRL processes. To address these gaps, we (a) collected trace data about student activities while working on a multi-source writing task and (b) analyzed these data using a cutting-edge learning analytic technique— ordered network analysis (ONA)—to model, visualize, and explain how learners' SRL processes changed in relation to the scaffolds. At the task level, our results suggest that learners who received adaptive scaffolding have significantly different patterns of SRL processes compared to the fixed scaffolding and control conditions. While not significantly different, our results at the task segment level suggest that adaptive scaffolding is associated with earlier engagement in SRL processes. At both the task level and task segment level, those who received adaptive scaffolding, compared to the other conditions, exhibited more task-guided learning processes such as referring to task instructions and rubrics in relation to their reading and writing. This study not only deepens our understanding of the effects of scaffolding at different levels of analysis but also demonstrates the use of a contemporary learning analytic technique for evaluating the effects of different kinds of scaffolding on learners' SRL processes.

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“…While communication accommodation and speech acts theories provide frameworks for understanding physician–nurse communication, ordered network analysis (ONA) 10 offers a novel methodology for objectively quantifying physician–nurse communication patterns. Building on methods of social and epistemic network analyses, ONA quantifies interactions in qualitative data.…”

Section: Introductionmentioning

confidence: 99%

Applying ordered network analysis to video-recorded physician–nurse interactions to examine communication patterns associated with shared understanding in inpatient oncology care settings

Popov,

Tan,

Manojlovich

2024

BMJ Open

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ObjectivesThe main aim of this study was to demonstrate how ordered network analysis of video-recorded interactions combined with verbal response mode (VRM) coding (eg, edification, disclosure, reflection and interpretation) can uncover specific communication patterns that contribute to the development of shared understanding between physicians and nurses. The major hypothesis was that dyads that reached shared understanding would exhibit different sequential relationships between VRM codes compared with dyads that did not reach shared understanding.DesignObservational study design with the secondary analysis of video-recorded interactions.SettingThe study was conducted on two oncology units at a large Midwestern academic health care system in the USA.ParticipantsA total of 33 unique physician–nurse dyadic interactions were included in the analysis. Participants were the physicians and nurses involved in these interactions during patient care rounds.Primary and secondary outcome measuresThe primary outcome measure was the development of shared understanding between physicians and nurses, as determined by prior qualitative analysis. Secondary measures included the frequencies, orders and co-occurrences of VRM codes in the interactions.ResultsA Mann-Whitney U test showed that dyads that reached shared understanding (N=6) were statistically significantly different (U=148, p=0.00, r=0.93) from dyads that did not reach shared understanding (N=25) in terms of the sequential relationships between edification and disclosure, edification and advisement, as well as edification and questioning. Dyads that reached shared understanding engaged in more edification followed by disclosure, suggesting the importance of this communication pattern for reaching shared understanding.ConclusionsThis novel methodology demonstrates a robust approach to inform interventions that enhance physician–nurse communication. Further research could explore applying this approach in other healthcare settings and contexts.

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Ordered Network Analysis

Cited by 15 publications

References 15 publications

Rethinking Undergraduate Computer Science Education: Using the 4Es Heuristic to Center Students in an Introductory Computer Science Course

Rethinking Undergraduate Computer Science Education: Using the 4Es Heuristic to Center Students in an Introductory Computer Science Course

Analytics of self-regulated learning scaffolding: effects on learning processes

Applying ordered network analysis to video-recorded physician–nurse interactions to examine communication patterns associated with shared understanding in inpatient oncology care settings

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