In the fall of 2022, 12 proposals were submitted to the Innovations in Teaching with Technology Awards. The Academic Technology Advisory Council awarded a total of $95,939 for the following four proposals.
A Tool to Self-Assess Language Proficiency to Improve Engagement and Facilitate Goals Setting
Giovanni Zimotti, director of Spanish Language Instruction, and Claire Frances, director of the Center for Language and Culture Learning, were awarded $15,200 to develop an app for language learners that will use the NCSSFL-ACTFL Can-Do Statements as well as questions from Learning at Iowa's Metacognitive Awareness Inventory to engage learners in self-assessment and metacognition and increase their self-regulation and sense of efficacy as learners.
Phase 2: AI Enabled Intelligent Assistant for Personalized and Adaptive Learning and Advising
Ibrahim Demir, associate professor of civil and environmental engineering, was awarded $30,067 for the second phase of the AI Enabled Intelligent Assistant (AIIA) for Personalized and Adaptive Learning and Advising project. The funds will be used to develop a prototype framework for an AI-Enabled Personalized Smart Assistant and pilot it in two courses (undergraduate and graduate).
Rodeostats: Lassoing Pythons in Lab
Johna Leddy, associate professor of chemistry, and Josh Coduto, graduate research assistant, were awarded $9,680 to develop undergraduate labs that introduce students to electrochemistry, a field that relates to energy and advanced technologies, such as batteries. Students will become familiar with the most popular instrument for electrochemists (the potentiostat) and work with Python to operate the open source hardware.
Building Learning Analytics Infrastructure to Provide Timely, Personalized Feedback
Adam Brummett, lecturer in chemistry, and Jane Russell, director of Office of Teaching, Learning, and Technology Research and Analytics, were awarded $40,992 to develop a learning analytics infrastructure that will aggregate and merge data created by students’ interactions with learning technologies to generate insights into engagement patterns with course materials and tools. This infrastructure will streamline the process for sending targeted messages to students based on behavioral and/or performance goals, supporting all students and lowering the barrier to providing personalized feedback in large courses.