Short-duration TPACK-based professional development improved teachers' ML knowledge and interest (ML4STEM)¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2023 · checked against its sources 2026-10-27 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? ML4STEM, a TPACK-based PD program using SmileyDiscovery, provides initial evidence that teachers can reach sufficient expertise to teach ML and gain interest in a short time. → H. Chad Lane 2023

Evidence¶

H. Chad Lane 2023¶

H. Chad Lane. (2023). Commentary for the International Journal of Artificial Intelligence in Education Special Issue on K-12 AI Education. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-023-00359-w

q2 · i? · review · r2

Evaluation of the ML4STEM professional development program, which the commentary reports included 18 teachers spread across grade levels in two 75-minute sessions framed as Teachers as Learners and Teachers as Designers. The commentary describes the TPACK-dimension evaluation as "very positive" with no effect sizes printed.

"A robust evaluation along the dimensions of the TPACK-based approach was very positive and stands as initial evidence that we can bring teachers up to a sufficient level of expertise in a relatively short amount of time to teach ML and improve their interest in doing so."

Discussion¶

Related Claims¶

• Team-based professional development is associated with shifts toward more student-centered teaching in qualitative studies, but not in one quantitative online-training study — related
• SDT-driven activity system redesign in Cycle 2 produced significant pre-post gains in AI-TPACK (d = 0.70), IPACK (d = 0.86), and AI attitude (d = 0.58) — related
• An online PD program using unplugged explainable machine-learning activities increased K–12 educators' AI self-efficacy from below-moderate to above-moderate levels — related
• A professional development masterclass produces a 24% overall improvement in educators' AI utilization competence with large effect sizes — related
• The study demonstrates the need for particular instructional supports, including differentiated expertise-building opportunities and addressing teacher beliefs about computational-model construction — related
• In-service mathematics teachers in the online TPACK program shifted from teacher-centered to valuing student-centered instructional strategies for teaching with technologies — related
• Professional learning experiences shift teachers' beliefs away from traditional views toward practice-based science and increase implementation confidence, with gains leveling off after initial workshops — related
• Teachers in online team-based training reported significantly greater confidence in their technological pedagogical content knowledge after training — related
• Teachers' confidence and interest in ML integration progressively increased from the Teachers-as-Learners to the Teachers-as-Designers session. — related
• Most participating teachers produce ML-empowered scientific discovery teaching ideas of excellent, good, or fair quality after the TaL session. — a narrower finding that bears on this claim
• The ML4STEM Teachers-as-Learners session significantly increases K-12 STEM teachers' technology knowledge of k-means clustering on five of six assessment questions. — a narrower finding that bears on this claim