Designing a System for Collecting and Analyzing Behavior Data of Instructors and Students in Blended Courses

Chen, Nan; Luo, Yangyang; Han, Xiao

doi:10.1109/eitt.2019.00019

Cited by 1 publication

(3 citation statements)

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“…These dimensions not only involve the main functions of OLTPs but are also the key links for teachers to use when carrying out information-based teaching or information integration (Howard et al , 2015). Combined with the commonly used analysis dimensions of online information behavior research (Han et al , 2019; Bommel et al , 2018; Chen et al , 2019a, b), the behavioral process data are quantified through the dimensions of richness, diversity, usefulness and timeliness.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, for indicators 3.2.3 and 3.3.2, although the teachers with high information literacy do not perform better, among those teachers who have developed stronger information teaching and research, these two aspects represent a higher level developmental direction or a higher requirement for the development of the teachers’ information literacy. Chen et al (2019a, b) also pointed out that enriching teachers’ information-related application situations is conducive to high-quality information activities.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, based on behavioral characteristics, indicators such as regularity, activity, availability and interactivity are reflected in the research. For example, the deviation was measured in resource-updating behaviors during each period to reveal regular patterns (Han et al , 2019); the activity level was calculated in each teacher group by the time spent discussing behaviors in the teacher learning community (Bommel et al , 2018); the availability was reflected of teachers’ educational resources by visits, collections and downloads (Dyckhoff et al , 2012; Chen et al , 2019a, b); and the interaction degree was quantified and classified of the learning community by the Social Network Analysis centrality index (Kim and Ketenci, 2019). Thus, when using the process data of teachers’ online information behaviors, different measurement dimensions can be adapted according to the research purpose.…”

Section: Background Literaturementioning

confidence: 99%

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Evaluation of teachers’ information literacy based on information of behavioral data in online learning and teaching platforms: an empirical study of China

Zhou

et al. 2021

LHT

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PurposeAdvances in information technology now permit the recording of massive and diverse process data, thereby making data-driven evaluations possible. This study discusses whether teachers’ information literacy can be evaluated based on their online information behaviors on online learning and teaching platforms (OLTPs).Design/methodology/approachFirst, to evaluate teachers’ information literacy, the process data were combined from teachers on OLTP to describe nine third-level indicators from the richness, diversity, usefulness and timeliness analysis dimensions. Second, propensity score matching (PSM) and difference tests were used to analyze the differences between the performance groups with reduced selection bias. Third, to effectively predict the information literacy score of each teacher, four sets of input variables were used for prediction using supervised learning models.FindingsThe results show that the high-performance group performs better than the low-performance group in 6 indicators. In addition, information-based teaching and behavioral research data can best reflect the level of information literacy. In the future, greater in-depth explorations are needed with richer online information behavioral data and a more effective evaluation model to increase evaluation accuracy.Originality/valueThe evaluation based on online information behaviors has concrete application scenarios, positively correlated results and prediction interpretability. Therefore, information literacy evaluations based on behaviors have great potential and favorable prospects.

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