Is Bloom's taxonomy appropriate for computer science?

Johnson, Colin G.; Fuller, Ursula

doi:10.1145/1315803.1315825

Cited by 56 publications

(21 citation statements)

References 3 publications

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“…Of particular interest is Johnson and Fuller's experiment showing a disconnect between the classification of freshman computer science test questions among educators and test writers [22]. The computer science educators did not classify many, if any, freshman test questions as meeting the higher-level educational objectives of analysis, evaluation, and synthesis stated in Bloom's taxonomy.…”

Section: Related Workmentioning

confidence: 99%

Using Bloom's taxonomy to code verbal protocols of students solving a data structure problem

Parham

Chinn

Stevenson

2009

Proceedings of the 47th Annual Southeast Regional Conference

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We describe a preliminary study exploring how computer science students solve a problem in an attempt to understand differences between the successful and the unsuccessful problem solver. Students followed a verbal protocol as they solved a data structures problem, and we analyzed the transcripts of these problem-solving sessions, classifying the statements students made using the revised Bloom's taxonomy. Based on our analysis in this case study, we conclude that the successful problem solver seems to move more frequently from one type of cognitive process to another than the unsuccessful problem solver. For the particular data structure problem the students attempted to solve, we observed that all problem solvers, successful or unsuccessful, tend to follow patterns in their problem-solving process.

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Section: Related Workmentioning

confidence: 99%

Using Bloom's taxonomy to code verbal protocols of students solving a data structure problem

Parham

Chinn

Stevenson

2009

Proceedings of the 47th Annual Southeast Regional Conference

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“…Given its popularity through the years, the taxonomy has been condensed, expanded and reinterpreted in a variety of ways (Forehand, 2012;Johnson and Fuller, 2006). The model was revised by Anderson et al (2001) with a number of significant changes to the terminology, structure and emphasis.…”

Section: The Bloom Taxonomy and Meaningful Learningmentioning

confidence: 99%

The Effectiveness of Robotics Competitions on Students’ Learning of Computer Science

KALOTI-HALLAK¹,

Armoni²,

Ben‐Ari³

2015

IOI

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Abstract. This work investigates students' learning of computer science (CS) as part of a research project on students' learning of and attitudes toward STEM (Science, Technology, Engineering, and Mathematics) subjects during their participation in robotics activities. The population consisted of groups of middle-school students (ages 13-15 years) who participated in the FIRST ® LEGO ® League competition. The methodology used is both qualitative and quantitative using questionnaires, observations and interviews during the school year 2012-2013, and mainly group interviews during the school year 2013-2014. A representational model was used during the interviews to facilitate externalizing the students' understanding of STEM concepts. The analysis used the revised Bloom Taxonomy (BT) to study the students' meaningful learning. Two CS concepts were investigated: input-output and interfacing with sensors. The results showed that during their preparation for the competition, almost all the students demonstrated meaningful learning, although some students reached higher levels of the BT than others.

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“…Learning taxonomies are important for computing education because it gives the community a vocabulary to use when discussing student understanding and learning -and curriculum to support that. Taxonomies The Revised Bloom's Taxonomy's value has been called into question in computer science [8] and has been modified to include "higher application" in order to make it relevant to the field [9].…”

Section: Related Workmentioning

confidence: 99%

The abstraction transition taxonomy

Cutts

Esper

Fecho

et al. 2012

Proceedings of the Ninth Annual International Conference on International Computing Education Research

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The abstraction transition taxonomy: developing desired learning outcomes through the lens of situated cognition. In: Clear, A., Sanders, K. {sesper, srfoster, mfecho, bsimon}@cs.ucsd.edu ABSTRACTWe report on a post-hoc analysis of introductory programming lecture materials. The purpose of this analysis is to identify what knowledge and skills we are asking students to acquire, as situated in the activity, tools, and culture of what programmers do and how they think. The specific materials analyzed are the 133 Peer Instruction questions used in lecture to support cognitive apprenticeship -honoring the situated nature of knowledge. We propose an Abstraction Transition Taxonomy for classifying the kinds of knowing and practices we engage students in as we seek to apprentice them into the programming world. We find students are asked to answer questions expressed using three levels of abstraction: English, CS Speak, and Code. Moreover, many questions involve asking students to transition between levels of abstraction within the context of a computational problem. Finally, by applying our taxonomy in classifying a range of introductory programming exams, we find that summative assessments (including our own) tend to emphasize a small range of the skills fostered in students during the formative/apprenticeship phase.

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Is Bloom's taxonomy appropriate for computer science?

Cited by 56 publications

References 3 publications

Using Bloom's taxonomy to code verbal protocols of students solving a data structure problem

Using Bloom's taxonomy to code verbal protocols of students solving a data structure problem

The Effectiveness of Robotics Competitions on Students’ Learning of Computer Science

The abstraction transition taxonomy

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