Details

Autor(en) / Beteiligte

• Haag, Maria
• Le Tourneau, Justin
• Marra, Rose
• Lamberson, William

Titel

PSVI-7 Feedback optimization: an iterative, value-added approach in a beef cattle breeding simulation

Ist Teil von

• Journal of animal science, 2019-07, Vol.97 (Supplement_2), p.237-237

Ort / Verlag

Champaign: Oxford University Press

Erscheinungsjahr

2019

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Abstract Understanding the systematic effects of genetic change is critical for any livestock producer. To help students learn about such changes we developed a beef cattle breeding simulation. This simulation features dynamic feedback designed to assist students in understanding their progress. Without feedback, students are often unable to make sense of their results which can inhibit their learning. The literature on feedback in simulations has shown varying effectiveness complexity levels, timing, and personalization. Oftentimes, this variation is associated with learner characteristics such as prior knowledge or gender. In our previous work, we determined that students did not always read feedback which reduces the likelihood of misconception reversal. Therefore, the aim of our current work was to identify feedback designs that ensure students are engaging with the material. To do this we designed two types of feedback: Static and Interactive. In Static feedback, students were simply shown the feedback and could click through—like the previous version. In Interactive feedback, students were required to answer a question regarding the feedback. We then assigned 242 students from 10 universities to one feedback type at random. We found that students in low and moderate performance groups using Interactive feedback showed higher (P = 0.06) posttest scores than those using Static feedback. No difference was observed in high performers which was expected according to the literature. This study demonstrated that feedback effectiveness is dependent on learner characteristics such as performance level. Thereby, developing feedback that is tailored to the student delivers a more personalized learning experience which can improve learning.