TY - GEN
T1 - Personalized guidance on how to review paper-based assessments
AU - Paredes, Yancy Vance
AU - Hsiao, Ihan
AU - Lin, Yiling
N1 - Publisher Copyright:
© 2018 Asia-Pacific Society for Computers in Education. All rights reserved.
PY - 2018/11/24
Y1 - 2018/11/24
N2 - Providing feedback is one of the most effective methods to enhance student's learning. The absence of readily available data on paper-based assessments makes it impossible to know whether students received feedback and whether they have acted upon it or not. In our institution, we have been using a homegrown educational technology to support blended-instruction classes by integrating physical and cyberlearning analytics. Using the collected digital footprints of students, we were able to analyze their reviewing behavior. A study was conducted to investigate the effects of personalizing the reviewing sequence of paper-based assessments. Each student is presented with a personalized sequence of questions to review based on the importance of their mistakes. We found that the students who followed the suggested sequence improved significantly higher in the succeeding exam than those who reviewed the assessment arbitrarily or did not have any reviewing strategy. Results showed that personalized guidance on reviewing graded assessments effectively helped improve student performance.
AB - Providing feedback is one of the most effective methods to enhance student's learning. The absence of readily available data on paper-based assessments makes it impossible to know whether students received feedback and whether they have acted upon it or not. In our institution, we have been using a homegrown educational technology to support blended-instruction classes by integrating physical and cyberlearning analytics. Using the collected digital footprints of students, we were able to analyze their reviewing behavior. A study was conducted to investigate the effects of personalizing the reviewing sequence of paper-based assessments. Each student is presented with a personalized sequence of questions to review based on the importance of their mistakes. We found that the students who followed the suggested sequence improved significantly higher in the succeeding exam than those who reviewed the assessment arbitrarily or did not have any reviewing strategy. Results showed that personalized guidance on reviewing graded assessments effectively helped improve student performance.
KW - Formal assessment
KW - Multimodal learning analytics
KW - Personalized feedback
KW - Personalized guidance
KW - Personalized learning
KW - Programming learning
UR - http://www.scopus.com/inward/record.url?scp=85060009934&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060009934&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85060009934
T3 - ICCE 2018 - 26th International Conference on Computers in Education, Main Conference Proceedings
SP - 257
EP - 265
BT - ICCE 2018 - 26th International Conference on Computers in Education, Main Conference Proceedings
A2 - Rodrigo, Ma. Mercedes T.
A2 - Yang, Jie-Chi
A2 - Wong, Lung-Hsiang
A2 - Chang, Maiga
PB - Asia-Pacific Society for Computers in Education
T2 - 26th International Conference on Computers in Education, ICCE 2018
Y2 - 26 November 2018 through 30 November 2018
ER -