Dalian Maritime University
Dr. Yang Gao is currently an associate professor at Dalian Maritime University (DMU). Prior to his appointment at DMU, he taught at San Jose State University and Kent State University. He got his Ph.D. from the School of Teaching, Learning & Curriculum Studies, Kent State University. Yang does research in TESOL, ESL teacher education, comparative education, and technical communication. His current projects center around EFL reading teacher beliefs and practices, sociolinguistics, and technical writing.
Teaching with tech, if works appropriately, will facilitate teachers in their instruction. Teaching with tech may appear in different forms, with the majority of teachers using technologies directly in their classrooms. However, preparing for the class and evaluating students’ performance with proper technologies can also be part of teaching with tech, as they indirectly facilitate teachers to plan, organize, and evaluate their instructional practice and student performance. In our presentation, we introduced Readizy, a reading diagnosis technology, to facilitate teachers with their reading instruction. Readizy is an artificial intelligence technology through facial expression recognition techniques to help EFL teachers evaluate the reading text and assess students’ reading proficiency. In response to how this technology facilitates teaching, we present our rationale in two aspects: Readizy helps teachers screen and select text materials that are fit to their students’ actual reading proficiency levels; it also helps teachers diagnose their students’ comprehension of the reading text through their emotions, including excitement, joy, anxiety, and boredom. In our actual presentation, we also report how this tech has worked in our sampled reading classes and provide attendees with a demo on how it works to help our reading instruction.