Students with low achievement can assume high-level responsibility for collectively accomplishing knowledge-building discourse in a supportive knowledge-building environment.¶

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2016 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? In a supportive knowledge-building environment, students with low achievement appeared able to assume high-level responsibility for collectively accomplishing knowledge-building discourse. → Yang 2016

Evidence¶

Yang 2016¶

Yang, Y., van Aalst, J., Chan, C.K.K., & Tian, W. (2016). Reflective assessment in knowledge building by students with low academic achievement. Intern. J. Comput.-Support. Collab. Learn. https://doi.org/10.1007/s11412-016-9239-1

q2 · i? · design · r2

Qualitative analysis of 148 notes across nine inquiry threads from 20 Grade 11 low-achieving students, coded using van Aalst's framework. The authors conclude students "appeared to be able to assume the high-level responsibility for collectively accomplishing knowledge-building discourse."

"Overall, the above results suggest that in a supportive knowledge-building environment, students in this class appeared to be able to assume the high-level responsibility for collectively accomplishing knowledge-building discourse."

Discussion¶

Related Claims¶

• Collaboration and synthesis indicators in Knowledge Forum increased over time among low-achieving students.
• Knowledge-building discourse improved significantly from before to during reflective assessment, with students contributing more explanation-seeking questions, explanations, and metacognitive questions and statements.
• Most inquiry threads produced by low-achieving students were classified as knowledge construction or knowledge building rather than knowledge sharing. — a narrower finding that bears on this claim
• Qualitative analysis identified three mediating processes in KBM: discourse-driven idea improvement, analytics-supported meta-reflection, and model construction for system refinement — related