Background. The Standards for Computer Science (CS) Teachers include indicators related to classroom practices. To assess teacher proficiency related to these indicators at scale, we created and pilot-tested a vignette-based measure of K-5 CS teacher proficiencies related to Standards 2, 4, and 5. Research Questions. Our two research questions were: 1) How difficult did teachers find the new measure, and how effectively did each item discriminate between high- and low-performers? 2) Which teacher characteristics predict scores on the new measure? Methodology. Our team developed three vignettes and carefully aligned associated questions to Standards 2, 4, and 5. After cognitive interviews with K-5 teachers and several rounds of revision, we pilot tested the instrument with 111 U.S. K-5 teachers. Couched in classical test theory, we assessed the measure’s reliability, and each item’s difficulty and discrimination values. We also collected preliminary evidence of validity. Key Findings. Scores on the measure were approximately normally distributed. Item difficulties ranged from .46 (somewhat difficult) to .95 (very easy). Item discrimination values ranged from .16 to .48. Cronbach’s alpha (𝛼 = .66) indicated the measure could be improved to increase reliability. Scores on the measure were positively correlated with teachers’ reported teaching awards, but were not predicted by any of the independent variables. Implications. This new measure of teacher proficiencies shows promising psychometric qualities, though additional revisions to the items are warranted. Once finalized, this measure could be used by practitioners to identify strengths and growth areas for future professional development.

Thu 19 Feb

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10:40 - 12:00
Building Capacity for K–12 CS and AI EducationPapers at Meeting Room 260-267
Chair(s): Nadia Najjar pc
10:40
20m
Talk
Piloting a Vignettes Assessment to Measure K-5 CS Teacher Proficiencies and GrowthK12
Papers
Joseph Tise Institute for Advancing Computing Education, Monica McGill Institute for Advancing Computing Education, Vicky Sedgwick Visions by Vicky, Laycee Thigpen Institute for Advancing Computing Education, Amanda Bell Computer Science Teachers Association
11:00
20m
Talk
Transforming Confusion into Diffusion: Advancing Machine Learning Education via Bottom-Up InstructionGlobalCER Best Paper
Papers
Carlos Cotrini ETH Zürich, Sverrir Thorgeirsson ETH Zurich, Jesus Solano ETH Zürich, Zhendong Su ETH Zurich
11:20
20m
Talk
The Impact of Misalignment between Student and Teacher Evaluation of Student Skills on Middle School Student Motivation in Computer ScienceK12
Papers
Sheila Foley University of Nebraska - Lincoln, Leen-Kiat Soh University of Nebraska-Lincoln, Colby Lamb University of Nebraska - Lincoln, Wendy Smith University of Nebraska - Lincoln
11:40
20m
Talk
Exploring K–12 Teacher Motivation to Engage with AI in EducationK12
Papers
Ethel Tshukudu San Jose State University, Katharine Childs University of Glasgow, Gaokgakala Alogeng CSEdBotswana, Emma R. Dodoo University of Michigan, Douglas R. Case San Jose State University, Tebogo Videlmah Molebatsi Kgale Hill Junior Secondary School