IALT professor receives funding for AI project on mesocredentials and student learning

IALT professor receives funding for AI project on mesocredentials and student learning

Rob Moore, assistant professor of educational technology and the director of the IDEATE Lab, recently received a Spencer Foundation Small Research Grant to examine learners’ intentions to complete the first MOOC (massive open online courses) in a mesocredential program. This study will be the first comprehensive analysis of learner intentions in mesocredential programs. External support, like that from the Spencer Foundation, is possible because of the technological and cultural strength of the University of Florida’s AI initiative. Research like Moore’s illustrate the creativity with which faculty associated with the Institute for Advanced Learning Technologies (IALT) are addressing tomorrow’s challenges.

Rob Moore is smiling with trees behind him. He is wearing a brown blazer with a blue button up shirt.

Rob Moore, Ph.D. 

A Human-Centered Approach

Using a learner-centered approach that combines learner intent with course outcomes instead of completion rates to evaluate effectiveness, Moore’s study will tell a more complete story of learner engagement and behavior within MOOCs than just end-of-course outcomes. Understanding learner intentions and behavior is the first step in supporting them in reaching their goals — which is important as mesocredential program offerings grow in popularity and stature. 

Moore’s study will dive deeper into how mesocredentials, as an evolution of the MOOC ecosystem, have significant potential to support alternative pathways to academic degrees. This study also builds on the mesocredential concept, which he introduced and defined as MOOC-based achievements that translate into academic credit in a 2022 Distance Education article.

AI at UF

Using a data set that includes hundreds of data points for the more than 35,000 learners enrolled in the MOOC, the HiPerGator supercomputer is allowing Moore to better understand the motivations of learners who enroll in MOOCs.

“With so many data points, we need to leverage techniques such as machine learning to efficiently analyze the data and identify learner behavior patterns,” said Moore.

“For instance, are there specific course behaviors that increase the likelihood of success in the MOOC? And the second challenge is around the ‘success’ rate of MOOCs. My study uses identifiable learner data that allows for the granular analysis of course predictors and outcomes. Understanding a student’s intention to complete a MOOC and if they were successful will allow us to make better learning recommendations — making online education more accessible for everyone.”

The University of Florida is making AI the centerpiece of a major initiative that combines world-class infrastructure, cutting-edge research, and a transformational approach to curriculum development and planning. At the College of Education, IALT faculty are researching, creating and disseminating advanced learning technologies that improve learning outcomes on an international scale.

“As AI tools become useful in studying problems of practice with very large data sets, such as the MOOC dataset in Dr. Moore’s research, assuring those tools are trained on data that truly represent the range of learners and their intentions is paramount,” said Tom Dana, IALT director and associate dean for academic affairs. “The Institute for Advanced Learning Technologies is the home to Dr. Moore’s lab, and we are committed to the transformation of teaching and learning through studying the application of technologies to authentic educational problems. Dr. Moore’s conceptualization of mesocredentials adds a promising dimension to understanding the professional learning intentions and needs of the adult learner, particularly in MOOC environments.”

Partnerships to Transform Education

With its focus on the diverse motivations of adult learners enrolling in MOOCs, Moore’s research is well suited for support from the Spencer Foundation, which has funded education research for over 50 years. The highly competitive Small Research Grant focuses on funding “rigorous, intellectually ambitious and technically sound research that is relevant to the most pressing questions and compelling opportunities in education.” 

Moore, who recently received the Charles M. Reigeluth Emerging Researcher Award, is lauded for his work on digital learning ecologies and for encouraging his fellow educational technology scholars to engage with big data. As a reviewer for this project noted, “Moore is an increasingly visible scholar in educational technology research and has been involved in the movement of more AECT-affiliated scholars into learning analytics and big data projects.”

“As an emerging scholar in the field, winning the Spencer research grant is a huge confidence boost,” said Moore.

“For the reviewers to see the same vision that I have for mesocredentials is humbling and exciting. This award is foundational for my career and will establish key pieces to my evolving research program of study. I am ecstatic that I will be to devote dedicated research time for the next two years doing a deep dive into mesocredentials.”

Hey Chatbot, tell me how kids can learn about AI

Hey Chatbot, tell me how kids can learn about AI

UF researchers and students hold summer camp for local children to make AI more accessible.

Soccer-bot, stress-bot and fashion-bot are just three examples of conversational apps created by middle schoolers using a unique digital interface developed by University of Florida researchers. AMBY, which stands for AI Made By You, was piloted this summer as a part of Camp DIALOGS, an NSF-funded project aimed at making artificial intelligence and computer science more accessible, particularly for students in lower-income areas. The camp is a joint effort between UF’s Herbert Wertheim College of Engineering and College of Education and aligns with the university’s integrated approach to AI. In addition to providing pathways for camp attendees to learn more about AI and computer science, the lesson activities and learning approaches developed for the camp will be made available to middle school teachers throughout Florida.

This story was originally published at news.ufl.edu.

AI mini-symposium showcases UF College of Education’s commitment to the field

AI mini-symposium showcases UF College of Education’s commitment to the field

The University of Florida College of Education hosted the AI in Education mini-symposium, serving as an opportunity for researchers, educators, administrators and industry representatives to discuss the trends and issues in AI in education. As UF moves to become the nation’s first comprehensive AI university, the College of Education’s Institute for Advanced Learning Technology is positioning itself as a notable partner in AI research and instruction.
Two people are standing and looking intently at information on a large screen on the wall. The one towards the front has their hand out and explains the information to the other.
A symposium participant explains their research

AI is truly in the air!

The response the symposium organizers have received from the community has been truly amazing!” said event organizer Pavlo “Pasha” Antonenko, an associate professor of educational technology and director of the NeurAL Lab. “What is really important is that the attendees represented so many different stakeholder groups. We had a number of local entrepreneurs join us, NVIDIA representatives, school leaders, people who work with FL policymakers in Tallahassee, and, of course, researchers from all over our state. You could observe emerging partnerships and collaborations during breakout groups and other networking sessions. AI is truly in the air!”

Faculty from the college presented in-progress applications of AI research. Anthony Botelho, assistant professor of educational technology, discussed using natural language processing and machine learning to create a parent-facing literacy screener to help close literacy gaps with at-home reading. Maya Israel, associate professor of educational technology and computer science education, shared outcomes from the first iteration of Camp DIALOGS. This two-week summer camp experience offers middle school students the opportunity to create spoken conversational apps while learning foundational computer science and artificial intelligence principles.

In posters, demo sessions and the course showcase, participants from the College of Education, College of Design Construction and Planning and the Herbert Wertheim College of Engineering shared projects and pedagogy that addressed AI education from early childhood through college. Antonenko was optimistic about what was shared during these sessions. “It is very exciting to see the new courses our COE faculty have developed on AI in education over the last year! Wanli Xing and David Therrialut‘s new courses are highly accessible, which is very important. Many people view AI as something that requires advanced data science skills, but the core concepts can be taught without such prerequisite knowledge. On the other hand, we are also offering exciting new courses that tie together AI and research methods— like Jinnie Shin‘s new courses on Computational Psychometrics and Natural Language Processing.

One pervasive idea was present throughout the day— making AI concepts accessible and relevant to learners of all ages and backgrounds. As AI is implemented through the totality of UF’s curriculum, the researchers and innovators at the College of Education are translating research into practice to dramatically improve learning outcomes for Gators and learners everywhere.

UF Researchers Earn Grant to Teach Middle Schoolers About Shark Teeth Using AI

UF Researchers Earn Grant to Teach Middle Schoolers About Shark Teeth Using AI

This story was originally published at news.ufl.edu and floridamuseum.ufl.edu.

With the goal of recruiting more students to STEM and computer science careers, a team from the University of Florida’s Thompson Earth Systems Institute (TESI), the College of Education and the Herbert Wertheim College of Engineering will partner with the Calvert Marine Museum in Maryland on a three-year, $1.3 million project funded by the National Science Foundation to teach Florida middle school teachers and students how to use artificial intelligence (AI) to identify fossil shark teeth.

Using a branch of AI called “machine learning,” humans will teach computers how to use shape, color and texture to identify the teeth of the extinct giant shark megalodon.

Like dinosaurs, sharks are a charismatic group of animals that excite students, says Bruce MacFadden, director of TESI and one of the project’s principal investigators. As a hotspot for fossil shark teeth, Florida is the perfect location for this kind of program. Additionally, teachers will have access to the Florida Museum of Natural History’s collection of tens of thousands of shark specimens.

“Sharks are the hook to get them interested and, with their simple morphology, are easy specimens to identify using AI. Once we have the students’ attention, we will be able to work on how machine learning can help them answer other scientific questions,” said MacFadden, who is also a distinguished professor and paleontologist at the museum.

Students will first be tasked to make scientific observations of various tooth characteristics to feed into the computer algorithm. Once students teach the computer how to identify megalodon teeth, they will use the same method to identify other types of sharks’ teeth found along Florida’s beaches and river bottoms.

Co-principal investigator Victor Perez, a UF alumnus and an expert on extinct sharks such as megalodon, is now a paleontologist at the Calvert Marine Museum in Maryland.

“Using sharks as examples, we hope to dispel some of the myths that go along with AI, so that students can better understand possible careers around technology and computer science,” Perez said.

A core component of the project will be annual professional development workshops where 76 middle school teachers will work alongside paleontologists, education researchers and engineers to develop standards-based lesson plans. Preference will be given to teachers from schools that receive Title I funds to provide additional resources for low-income students. The customizable lesson plans and interactive machine learning models will be available on the project’s website for any teacher to access for free.

“The lesson plans developed by teachers and the project team will integrate science content, computer science and engineering skills, and discovery of career pathways for the benefit of middle school teachers and their students,” said Pasha Antonenko, associate professor of educational technology in the UF College of Education, and one of the project’s co-principal investigators.

“With this project, we will not only enhance students’ interest in science, but also introduce them to machine learning methods.”

The teachers will be recruited through TESI’s Scientist in Every Florida School (SEFS) program, which was one of eight pilot projects launched in 2019 with funding from UF’s Moonshot Initiative. SEFS is the first statewide program of its kind that matches working researchers with K-12 classrooms in the state. More than 900 teachers have participated in SEFS since its launch in 2019.

“We have developed close relationships with teachers and school districts in 41 counties and counting,” said Brian Abramowitz, K-12 education and outreach coordinator for SEFS. “The teachers have come to know and trust our professional development programs, and we are excited to recruit them for this exciting new venture.”

The project helps further the university’s goal of becoming a national leader of AI development and application. UF is currently home to the most powerful university-owned supercomputer in the U.S.

Co-principal investigator Jeremy Waisome, an instructional assistant professor in the UF Herbert Wertheim College of Engineering, will be responsible for helping students and teachers develop and understand machine learning models. At the same time, the team will be analyzing student and teacher perceptions of AI in science.

“We hope to understand ways to integrate AI in science classrooms that are accessible, engaging and exciting,” Waisome said. “We believe this foundational knowledge will inspire students to consider careers in STEM.”

Bruce MacFadden, bmacfadd@flmnh.ufl.edu, 352-362-3072
Pasha Antonenko, p.antonenko@coe.ufl.edu, 352-273-4176
Brian Abramowitz, babramowitz@floridamuseum.ufl.edu, 516-225-9390
Jeremy Waisome, jwaisome@eng.ufl.edu

Rebecca Burton, rlburton@floridamuseum.ufl.edu, 850-316-1555

Featured image:
Victor Perez holds tooth of extinct giant shark Megalodon. Florida Museum photo by Kristen Grace

Victor Perez holds tooth of extinct giant shark Megalodon

Victor Perez holds tooth of extinct giant shark Megalodon

UF faculty receive NSF grant to develop a novel, AI-enhanced gaze-driven learning technology

UF faculty receive NSF grant to develop a novel, AI-enhanced gaze-driven learning technology

Multimedia has long been considered a powerful tool in instruction, but University of Florida researchers believe differences in learners’ visual attention and cognition can impact just how effective multimedia environments are in fostering learning outcomes for all.

Pavlo “Pasha” Antonenko, associate professor of educational technology and director of the Neuroscience Applications for Learning (NeurAL) Lab, and a team of researchers have received $821,412 from the National Science Foundation to design and test a novel, artificial intelligence (AI)-enabled gaze-driven adaptive learning technology that provides individualized multimedia learning support to students in real-time based on differences in their working memory capacity and visual attention patterns.

Working memory capacity provides the attentional control needed to select, organize and integrate information that is gained from multimedia materials such as text, video, audio or graphics. As learners have unique strengths and weaknesses, they too have differences in working memory capacity and the visual attention strategies that can either facilitate or hinder learning.

Pasha Antonenko

Pavlo “Pasha” Antonenko, Ph.D. 

“We assume that just because we’ve designed a nice PowerPoint or Google Slides presentation all students will effectively and efficiently understand everything, but in fact that’s not what happens because we do have a lot of individual differences that impact the way we learn,” said Antonenko, principal investigator of the project.

To address this gap, Antonenko will work alongside co-principal investigators Jonathan Martin, professor of geology, Kara Dawson, professor of educational technology, and Albert Ritzhaupt, professor of educational technology and computer science education, to develop GeoGaze — a display technology powered by AI that uses eye tracking to change multimedia learning materials in real-time based on students’ gaze behavior and differences in their working memory capacity. Marc Pomplun, principal investigator of the project’s sub-award and professor and chair of computer science at the University of Massachusetts Boston, will serve as the project’s eye tracking expert.

Using AI, GeoGaze will analyze and predict effective visual attention strategies for each student and then in real-time adapt the presentation of information to better support their learning.

“It’s a dangerous assumption, but we assume that if we show a person a screen that has some text and has a diagram, that they’re actually going to pay attention to either or both of these information sources,” Antonenko said. “… What we are finding in our eye tracking studies is — no — that’s not the case.”

The project, titled “Collaborative Research: GeoGaze: Gaze-Driven Adaptive Multimedia to Augment Geoscience Learning for Neurodiverse Learners,” will involve two studies, each enlisting 200 UF and Santa Fe College students. Study one will investigate students’ eye movement patterns while viewing a geoscience presentation on sea level rise and examine the different levels of learners’ working memory capacity to identify the best visual attention strategies needed to support their learning. Study two will then leverage these findings to build and optimize the machine learning algorithm and the actual GeoGaze technology with a large sample of postsecondary students viewing geoscience content.

Antonenko shared that the team hopes the AI-powered technology will advance the science of adaptive learning and help educators everywhere to provide students with needed personalized learning support in real-time.

“It’s important to individualize learning so when the time comes for us to actually pay attention to some information on the screen, which we do individually, we want to make sure that every student is supported based on their unique blend of individual differences in attention and cognition,” Antonenko said. “So, to say that students who need more support are in fact supported, and if we can have a technology that helps provide that support — well even better.”

The project is expected to be completed in 2024.

Jonathan Martin

Jonathan Martin, Ph.D. 

Kara Dawson

Kara Dawson, Ph.D. 

Albert Ritzhaupt

Albert Ritzhaupt, Ph.D. 

Marc Pomplun

Marc Pomplun, Ph.D.