ICAP-Bloom adapted coding scheme for cognitive engagement in online discussion posts¶

Theory · All theories
Evidence · 6 claims (5 for, 1 mixed) · 2 studies (2 design), q2 · 0 of 2 report an effect size · 6 claims rest on one study

Description¶

The authors adapted the ICAP framework by merging it with Bloom's revised taxonomy to label cognitive engagement in discussion posts. Four hierarchical categories were used: social, active, constructive, and interactive, with passive engagement excluded because it cannot be observed in produced posts. Active engagement corresponds to remembering and understanding (paraphrasing, mapping resources), constructive to applying and analyzing (compare, contrast, illustrate, argue), and interactive to evaluating and creating. As they state, "Interactive engagement relates to the levels of evaluating and creating in the taxonomy because these discussion posts make judgments and evaluations about the topics covered." Two coders reached .91 inter-rater agreement.

Design Implications¶

Context¶

Requirements¶

• Posts must be produced text (passive engagement cannot be coded); coding assigns the highest engagement level observed in each post, informed by Bloom's taxonomy level indicators.

Constraints¶

• The scheme was developed and applied to fully online graduate-level course forums; the authors note a lack of consensus concerning ICAP coding schemes for online environments.

Target Learners¶

• graduate students in fully online courses

Target Learning Objectives¶

• identifying levels of cognitive engagement in discussion forum posts

Claims¶

• Classifiers systematically confuse adjacent engagement levels: social with active, constructive with interactive, and interactive with active [~W]
• Discipline-general academic vocabulary (AWL use) supports cognitive engagement identification and may aid generalization across courses [+W]
• Academic word list count, word count, and Flesch-Kincaid grade level are the most important features for predicting cognitive engagement in discussion posts [+W]
• All three trained classifiers outperformed the zero-rule baseline (28.4% accuracy) for classifying cognitive engagement in discussion posts [+W]
• A support vector machine classifier outperformed decision tree and random forest models in predicting cognitive engagement levels of online discussion posts [+W]
• The ICAP Framework was found effective for assessing potential for active learning in an asynchronous online environment and identifying where design improvements are needed [+W]

Related Theories¶

• Revised ICAP Framework embedding formative feedback in each engagement mode for asynchronous online learning
• Bloom's Taxonomy as a six-level scheme for classifying the cognitive level of multiple-choice questions
• Revised Bloom's Taxonomy process dimensions as a framework for framing value education objectives
• Bloom's Taxonomy
• ICAP framework: four engagement modes from Interactive to Passive

Examples¶

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Key Sources¶

• Gorgun, G., Yildirim-Erbasli, S. N., & Demmans Epp, C. (2022). Predicting cognitive engagement in online course discussion forums. Proceedings of the 15th International Conference on Educational Data Mining. https://doi.org/10.5281/zenodo.6853149