Computers and Education: Artificial Intelligence

06 Jan 2023

Computers and Education: Artificial Intelligence

This study developed an interactive test dashboard with diagnosis and feedback mechanisms (ITD-DFM) that can
generate visualized, rich, and high-quality test feedback for each learner’s learning reflection and review based on
simultaneously considering test response time and correctness to assist students’ learning. A quasi-experimental
research was conducted with 50 Grade 8 students from two classes in a public junior high school in Taiwan to
assess the learning performance of ITD-DFM. One class with 26 students was assigned to the experimental group
using the ITD-DFM to support learning, whereas the other class with 24 students was assigned to the control group
using the traditional test system without diagnosis and feedback mechanisms (TTS-NDFM). Experimental results
reveal that the learning performance, physics self-efficacy, and technology acceptance of the experimental group
were significantly better than those of the control group. The ITD-DFM has the same effect on promoting the
learning performance of learners with different prior knowledge levels as well as learners with either high or low
prior knowledge level in the experimental group exhibited significant improvement in physics self-efficacy, but no
such results in the control group. The ITD-DFM provides more benefit in promoting the technology acceptance of
learners with high prior knowledge level.

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