Abstract
| Original language | English |
|---|---|
| Article number | 116 |
| Number of pages | 14 |
| Journal | Frontiers in Education |
| Volume | 3 |
| DOIs | |
| Publication status | Published - 4 Jan 2019 |
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Automated Feedback Can Improve Hypothesis Quality. / Kroeze, Karel A. (Corresponding Author); Van Den Berg, Stéphanie M.; Lazonder, Ard W.; Veldkamp, Bernard P.; de Jong, Ton.
In: Frontiers in Education, Vol. 3, 116, 04.01.2019.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Automated Feedback Can Improve Hypothesis Quality
AU - Kroeze, Karel A.
AU - Van Den Berg, Stéphanie M.
AU - Lazonder, Ard W.
AU - Veldkamp, Bernard P.
AU - de Jong, Ton
PY - 2019/1/4
Y1 - 2019/1/4
N2 - Stating a hypothesis is one of the central processes in inquiry learning, and often forms the starting point of the inquiry process. We designed, implemented, and evaluated an automated parsing and feedback system that informed students about the quality of hypotheses they had created in an online tool, the hypothesis scratchpad. In two pilot studies in different domains (“supply and demand” from economics and “electrical circuits” from physics) we determined the parser's accuracy by comparing its judgments with those of human experts. A satisfactory to high accuracy was reached. In the main study (in the “electrical circuits” domain), students were assigned to one of two conditions: no feedback (control) and automated feedback. We found that the subset of students in the experimental condition who asked for automated feedback on their hypotheses were much more likely to create a syntactically correct hypothesis than students in either condition who did not ask for feedback.
AB - Stating a hypothesis is one of the central processes in inquiry learning, and often forms the starting point of the inquiry process. We designed, implemented, and evaluated an automated parsing and feedback system that informed students about the quality of hypotheses they had created in an online tool, the hypothesis scratchpad. In two pilot studies in different domains (“supply and demand” from economics and “electrical circuits” from physics) we determined the parser's accuracy by comparing its judgments with those of human experts. A satisfactory to high accuracy was reached. In the main study (in the “electrical circuits” domain), students were assigned to one of two conditions: no feedback (control) and automated feedback. We found that the subset of students in the experimental condition who asked for automated feedback on their hypotheses were much more likely to create a syntactically correct hypothesis than students in either condition who did not ask for feedback.
U2 - 10.3389/feduc.2018.00116
DO - 10.3389/feduc.2018.00116
M3 - Article
VL - 3
JO - Frontiers in Education
JF - Frontiers in Education
SN - 2504-284X
M1 - 116
ER -