Chang to receive Messick award for ‘significant, enduring contributions to quantitative research’
Hua Hua Chang is the 2024 recipient of the highly prestigious Samuel J. Messick Distinguished Scientific Contributions Award from the American Psychological Association (APA) Division 5.
“This award holds a deep personal significance for me, acknowledging the long journey and effort invested in my research,” said Chang, the Charles R. Hicks Professor of Educational Psychology and Measurement in the College of Education’s Department of Educational Studies. “It’s also significant because it highlights the potential impact my work can have on quantitative psychology. This recognition motivates me to keep striving for further advancements and inspires others to pursue their own scientific endeavors.”
Established by the Educational Testing Service (ETS) in memory of Dr. Samuel J. Messick, this prestigious award is bestowed annually to acknowledge individuals who have made significant and enduring contributions to scientific research in quantitative research methods.
“I am deeply honored and humbled to be the recipient of the 2024 APA Division 5 Samuel J. Messick Award,” Chang said. “During my tenure at ETS from 1992 to 1998, although I did not have direct interaction with Dr. Messick, his writings and insights consistently guided my research in the field of testing and assessment. As a professor teaching measurement for 25 years, one aspect that has resonated profoundly with me is Dr. Messick’s construct validity theory.”
Chang’s research on computerized adaptive testing (CAT) has been particularly impactful as he developed novel algorithms that have revolutionized how personalized assessments are conducted, leading to more efficient and accurate evaluations.
“Professor Hua Hua Chang is recognized internationally as a leading scholar in computerized adaptive testing and other aspects of machine learning in education measurement,” noted Wayne E. Wright, the College’s associate dean for research, graduate programs, and faculty development. “He is most deserving of this highly prestigious award. ”
Chang envisions extending computerized adaptive testing (CAT) to the learning domain. His ongoing work highlights the potential of CAT data to inform generative artificial intelligence (AI) systems, allowing them to tailor learner feedback effectively. The increased visibility from this award will be crucial to him in securing the resources needed to develop and test a prototype system utilizing CAT data for personalized learning through AI.
At the 2024 APA convention in Seattle, WA, Chang will give a 15-minute presentation at the award ceremony on August 9 and will receive the award.
Source: Hua Hua Chang, chang606@purdue.edu