Information Behaviors and Cognitive Modes Used for Cyber Situation Assessment

Situation assessment is a critical skill amongst electricity distribution controllers but can be difficult to assess in practice. In the present research, we adapted a psychometric approach based on the principle that expert situation assessment engages cue-based associations from memory. Using consortium norming, we acquired performance data from 320 network control operators for five network control-related tasks that comprised the electricity network service provider edition of the EXPERT Intensive Skills Evaluation (EXPERTise 2.0) software. Operators were distributed across 11 Distributed Network Service Providers (DNSP), with data collected over three phases. Data were examined across the three phases of data collection and suggest that DNSPs can monitor the situation assessment of network controllers at an individual and at an organisational level, affording the opportunity to identify changes in performance and implement remedial strategies as appropriate.

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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

Library Hi Tech ◽

10.1108/lht-01-2021-0034 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Yating Li ◽

Chi Zhou ◽

Di Wu ◽

Min Chen

Keyword(s):

Online Learning ◽

Information Literacy ◽

High Performance ◽

Behavioral Data ◽

Online Information ◽

Process Data ◽

Content Type ◽

Information Behaviors ◽

Learning And Teaching ◽

Performance Group

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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