‘Technology-enabled self-regulation’: Professor Eunice Eunhee Jang on the educational potential of BalanceAI

November 26, 2021

 

By Lisa Smith

 

 

Eunice Eunhee Jang presented The Power of Diagnostic Scaffolding in Technology-Rich Learning-Oriented Assessment Environments at a Focus on Research session hosted by OISE’s Office of the Associate Dean, Research, International & Innovation. 

 

On November 11, Professor Eunice Eunhee Jang introduced the potential of BalanceAI to an online audience of over 70 OISE faculty, students, staff, and postdoctoral fellows. A SSHRC-funded assessment program developed by Jang and her team, BalanceAI uses artificial intelligence to provide adaptive feedback in real time as students complete learning tasks.  

 

Since 2016, Jang has been researching the impact of BalanceAI on language and literacy skills of over 400 students from grades 3-6 in diverse educational settings, including tutoring programs for children from urban shelters and immigrant families.  She has partnered with the Toronto District School Board, the Dr. Eric Jackman Institute of Child Study, Associated Hebrew Schools, the University of Toronto Schools Bridge Program, Afghan Women’s Organization Refugee and Immigrant Services, and the Toronto Chapter of CAUSE Tutoring.

 

Although impressive, it is perhaps not surprising that Artificial Intelligence (AI)-informed technology is a powerful assessment tool. Jang outlined how machine learning technology can automate the assessment of papers and presentations while providing data visualization tools that capture learning trajectories of individual students.

 

What is particularly innovative is how the BalanceAI program can lead to better learning outcomes and codirect both teaching and learning. By providing real-time feedback, BalanceAI ‘coaches’ students to organize their own learning. Students in Jang’s study were asked questions to encourage active reading and were prompted to check their work before submitting it for evaluation. Before long, students began to assess and revise their work on their own without external prompting. Students were learning how to learn while developing language and literacy skills.

 

In turn, teachers were able to see individual students’ areas of strength, their learning needs, and how to tailor individual lessons to meet those needs. Some students may need to work on metacognitive skills supporting literacy. Others need extra support for developing basic literacy skills. In effect, BalanceAI shines a light on the invisible processes behind literacy. In Professor Jang’s terms, AI “affords possibilities for co-adaptation among learning agents” and potentially “redesigns the relationship between learning and assessment.”