Both experimental and control groups improved significantly on all questions and conceptual questions from pre- to post-test after using PyKinetic¶
Claim · All claims
Evidence · 1 study (2 entries) · causalr2·q3
Currency · newest study 2019 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q3 i? Participants from both groups improved their scores significantly between pre- and post-test on all questions and on conceptual questions, providing evidence that PyKinetic supported learning. → Fabic 2019
q3 i? There was no significant improvement on procedural questions only. → Fabic 2019
Evidence¶
Fabic 2019¶
Fabic, G. V. F., Mitrovic, A., & Neshatian, K. (2019). Evaluation of Parsons Problems with Menu-Based Self-Explanation Prompts in a Mobile Python Tutor. International Journal of Artificial Intelligence in Education, 29, 507–535. https://doi.org/10.1007/s40593-019-00184-0
q3 · i? · causal · r2
Controlled study with 63 participants from two universities using PyKinetic for about an hour. Wilcoxon Signed Ranks tests showed significant pre/post improvement on all questions (experimental W = 379, p = .000; control W = 483, p = .002) and conceptual questions, but not procedural questions only.
"Participants from both groups improved their scores significantly between the pre- and post-test (the Improvement on All Questions row), and on conceptual questions (the Improvement Conceptual row), but there was no significant improvement on procedural questions only."
Fabic 2019 (2)¶
Fabic, G. V. F., Mitrovic, A., & Neshatian, K. (2019). Evaluation of Parsons Problems with Menu-Based Self-Explanation Prompts in a Mobile Python Tutor. International Journal of Artificial Intelligence in Education, 29, 507–535. https://doi.org/10.1007/s40593-019-00184-0
q3 · i? · causal · r2
The article reports positive Cohen's d effect sizes for both groups on all questions, noting that "the effect size was higher for the experimental group" (d = .89 experimental vs. d = .55 control as printed in Table 6).
"Both groups had a positive Cohen's d effect size, but the effect size was higher for the experimental group."
Discussion¶
Related Claims¶
- Low prior knowledge students learned more from PyKinetic's Parsons problems than high prior knowledge students, especially in the experimental group with SE prompts — related
- Both instructional groups improved significantly from pre-test to post-test, with larger gains in the generative AI-supported group — related
- Both sequencing groups improved in conceptual and procedural knowledge, with no significant group-by-time interaction — related
- Both groups improved significantly on harder-to-guess questions, and the experimental group outperformed the control group on them at post-test — a narrower finding that bears on this claim
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
pykinetic-improves-python-learning |
title |
Both experimental and control groups improved significantly on all questions and conceptual questions from pre- to post-test after using PyKinetic |
description |
Both experimental and control groups improved significantly on all questions and conceptual questions from pre- to post-test after using PyKinetic |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2019 |
generated |
by process:wiki-ingest on 2026-10-28 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — fabic-2019, fabic-2019-2 |
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