Educational Technology Commons^™

The Manifesto For Teaching And Learning In A Time Of Generative Ai: A Critical Collective Stance To Better Navigate The Future, Aras Bozkurt, Junhong Xiao, Robert Farrow, John Y. H. Bai, Chrissi Nerantzi, Stephanie Moore, Jon Dron, Christian M. Stracke, Lenandlar Singh, Helen Crompton, Apostolos Koutropoulos, Evgenii Terentev, Angelica Pazurek, Mark Nichols, Alexander M. Sidorkin, Eamon Costello, Steven Watson, Dónal Mulligan, Sarah Honeychurch, Charles B. Hodges, Mike Sharples, Andrew Swindell, Isak Frumin, Ahmed Tlili, Patricia J. Slagter Van Tryon, Melissa Bond, Maha Bali, Jing Leng, Kai Zhang, Mutlu Cukurnova, Thomas K. F. Chiu, Kyungmee Lee, Stefan Hrastinski, Manuel B. Garcia, Ramesh Chander Sharma, Bryan Alexander, Olaf Zawacki-Richter, Henk Huijser, Petar Jandrić, Chanjin Zheng, Peter Shea, Josep M. Duart, Chryssa Themeli, Anton Vorochkov, Sunagül Sani-Bozkurt, Robert L. Moore, Tutaleni Iita Asino

STEMPS Faculty Publications

This manifesto critically examines the unfolding integration of Generative AI (GenAI), chatbots, and algorithms into higher education, using a collective and thoughtful approach to navigate the future of teaching and learning. GenAI, while celebrated for its potential to personalize learning, enhance efficiency, and expand educational accessibility, is far from a neutral tool. Algorithms now shape human interaction, communication, and content creation, raising profound questions about human agency and biases and values embedded in their designs. As GenAI continues to evolve, we face critical challenges in maintaining human oversight, safeguarding equity, and facilitating meaningful, authentic learning experiences. This manifesto emphasizes that …

Classification Of Instructional Activities In Classroom Videos Using Neural Networks, Jonathan K. Foster, Matthew Korban, Peter Youngs, Ginger S. Watson, Scott T. Acton

VMASC Publications

Classroom videos have become an integral part of classroom observation and instructional quality studies. Researchers encounter substantial financial and time-consuming costs gathering trained personnel to catalogue and analyze a large quantity (i.e., hundreds of hours) of classroom videos. In this chapter, we argue that deep-learning neural networks have potential to help with these tasks by detecting features of instruction in videos. We evaluated the performance of three neural networks in detecting instructional activities in classroom videos. The video dataset included a total of forty-six hours, which was evenly split between elementary mathematics and English language arts lesson recordings. Results showed …

Automated Classification Of Elementary Instructional Activities: Analyzing The Consistency Of Human Annotations, Jonathan K. Foster, Peter Youngs, Rachel Van Aswegen, Samarth Singh, Ginger S. Watson, Scott T. Acton

VMASC Publications

Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos more efficient. These advances include natural language processing, automated speech recognition, and deep neural networks. To train artificial intelligence to accurately classify activities in classroom videos, humans must first annotate a set of videos in a consistent way. This paper describes our investigation of the degree of inter-annotator reliability …

Automatic Classification Of Activities In Classroom Videos, Jonathan K. Foster, Matthew Korban, Peter Youngs, Ginger S. Watson, Scott T. Acton

VMASC Publications

Classroom videos are a common source of data for educational researchers studying classroom interactions as well as a resource for teacher education and professional development. Over the last several decades emerging technologies have been applied to classroom videos to record, transcribe, and analyze classroom interactions. With the rise of machine learning, we report on the development and validation of neural networks to classify instructional activities using video signals, without analyzing speech or audio features, from a large corpus of nearly 250 h of classroom videos from elementary mathematics and English language arts instruction. Results indicated that the neural networks performed …

Enhancing Decision-Making In Higher Education: Exploring The Integration Of Chatgpt And Data Visualization Tools In Data Analysis, Tristan Jiang, Elina Liu, Tasawar Baig, Qingrong Li

University Administration Publications

This chapter explores the potential of integrating conversational AI tools such as ChatGPT with data visualization (DV) tools such as Power BI in higher education settings. A brief history of chatbots is summarized and challenges and opportunities in higher education are outlined. The highlights include AI's prospects for enhancing data-informed decision-making while needing safeguards to mitigate risks. Through a pioneering exercise, we integrated ChatGPT's conversational capabilities with Power BI's interface via API and tested functionality. Suggestions for good practice and implications for higher education are discussed.

Smart Learning Development Model Of Indonesian Higher Education, Jajat Sudrajat, Widodo Samyono

Mathematics & Statistics Faculty Publications

This research aims to provide input to the Entrepreneurship Study Program to improve the learning process in the context of accelerating National Entrepreneurship so that it can be implemented in 59 Entrepreneurship Study Programs that are members of the apski.net, as a follow-up to the Focus Group Discussion with members of APSKI and KEMENKOPEKM. The research method used in this study is the Research and Development (R&D) method through a case study of the intelligent learning process in the Entrepreneurship Study Program, Bina Nusantara University (Binus). The result of this research is that the Entrepreneurship Study Program can brand entrepreneurship …

The Educational Affordances And Challenges Of Chatgpt: State Of The Field, Helen Crompton, Diane Burke

STEMPS Faculty Publications

ChatGPT was released to the public in November 30, 2022. This study examines how ChatGPT can be used by educators and students to promote learning and what are the challenges and limitations. This study is unique in providing one of the first systematic reviews using peer review studies to provide an early examination of the field. Using PRISMA principles, 44 articles were selected for review. Grounded coding was then used to reveal trends in the data. The findings show that educators can use ChatGPT for teaching support, task automation, and professional development. These were further delineated further by axial sub …

From Fixed To Growth: How A Mindset Transforms Student Learning, Andrew Fabo

Williams Honors College, Honors Research Projects

Placing labels onto young learners, such as “smart” and “gifted,” impacts their brain growth and mental health tremendously; rarely in a positive manner. This way of thinking, formed by separating students into “accelerated” and “normal” categories, can instill what is known as a fixed mindset of learning. Believing that there is no room to grow, or being afraid to make mistakes, largely due to the impact of these labels, learners quickly become less likely to attempt more challenging tasks; as well as persevere through difficult obstacles. Through extensive research within the Akron-Summit County Public Library, The University of Akron’s Bierce …

Development Of A Safety Performance Decision-Making Tool For Flight Training Organizations, Marisa Aguiar, Carolina L. Anderson, Dothang Truong, Gregory S. Woo, Kenneth Byrnes

Journal of Aviation/Aerospace Education & Research

The purpose of the research was to create and validate a safety performance decision-making tool to transform a reactive safety model into a predictive, decision-making tool, specific to flight training organizations, to increase safety and aid in operational decision-making. Using Monte Carlo simulation, the study conducted simulation runs based on operational ranges to simulate the operating conditions with varying levels of controllable resources in terms of personnel (Aviation Maintenance Technicians and Instructor Pilots) and expenditures (active flight students and available aircraft). Four What-if Scenarios were conducted by manipulating the controllable inputs. Changes to the controllable inputs are reflected by variations …

Gender Differences In Achievement, Behavior, And Stem Interest Among Learners Using Minecraft, Maricel A. Esclamado, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

In this paper, we analyze how male and female learners differ in their in-game behaviors, knowledge assessment outcomes, and STEM interest using the What-If Hypothetical Implementations using Minecraft (WHIMC). We also investigate how male and female learners’ self-reported levels of frustration and boredom relate to these outcomes. We examine in-game data, out-of-game assessment data, self-reported frustration and boredom, and results of the STEM interest questionnaire (SIQ) from 175 Grade 8 learners from a school in the Philippines. We found that male learners tend to explore more than female learners. Both genders learn more through more exploration, making more observations, and …

Exploring I-Ready Mathematics And Its Support For Learning Fractions Of Third Grade Students, Allison Carnesale

Honors Undergraduate Theses

This study explores the effectiveness of the i-Ready Mathematics program in enhancing third-grade students’ understanding of fractions through a mixed-methods approach. Utilizing an explanatory sequential design, this research combines quantitative analysis of student diagnostic and F.A.S.T. assessment scores in mathematics with qualitative observational data. The study aims to assess whether i-Ready serves as a supportive tool for fraction learning and identify behavioral factors influencing student engagement.

Conducted over a three-month period in one third grade classroom, the study followed five students engaged with i-Ready’s fraction-focused lessons. Quantitative findings indicated that most students demonstrated academic growth, as evidenced by upward trends …

Influences Of Professors' Personality Traits, Teaching Styles, And Generational Affiliation On Technology Acceptance: A Mixed-Methods Exploration Of Blended Learning Readiness, Joey K. Freeman

Education Dissertations

The abrupt transition to emergency remote teaching during the COVID-19 pandemic offered minimal time to prepare, resulting in faculty reliance on prior pedagogical practices in the shift to an online instructional environment. Although the pandemic altered the learning environment in the short-term, it also offered a glimpse of how higher education institutions (HEIs) could transform their learning environments in the long-term. Though a body of literature exists on factors that influence technology acceptance, a limited number of studies have explored personality traits, teaching styles, and generational affiliation. An adapted Technology Acceptance Model considered these variables as antecedents to perceptions, attitudes, …

Evaluating Ai In Teacher Performance Reviews: Benefits, Biases, And Best Practices, Eric Silberberg

Open Educational Resources

View the tutorial at: https://esilberberg.github.io/AI-Teacher-Reviews-Lesson/

In this tutorial, you'll try your hand at building your own AI tools that analyze sentiment in student feedback with the Google Gemini LLM and Python. Through experience using the technology, you'll better understand the benefits, biases, and best practices of this approach to teacher performance evaluations. You'll learn how to:

1. Configure the Gemini API, integrate it into Python functions, and analyze a set of student feedback with these functions.
2. Refine function output by way of prompt engineering.
3. Critically analyze the use of AI in teacher performance reviews.

Ai And English Language Teaching: Affordances And Challenges, Helen Crompton, Adam Edmett, Neenaz Ichaporia, Diane Burke

STEMPS Faculty Publications

English is one of the most used languages for jobs, markets, tourism, discourse and international connectivity. However, English learners face many challenges in gaining English language skills. Extant studies show that AI has affordances to support in English language teaching and learning ELT/L. This study answers the call to examine specific challenges and affordances for using AI in ELT/L. A systematic review method was used with PRISMA principles to identify 42 studies. Findings reveal the geographical locations of studies, learner ages and years of study. Grounded coding was then used to identify affordances of the use of AI in ELT/L …

The Nexus Of Iste Standards And Academic Progress: A Mapping Analysis Of Empirical Studies, Helen Crompton, Diane Burke

STEMPS Faculty Publications

Technology has become commonplace in K-12 classrooms with students actively using digital technology to support learning. The purpose of this study was to investigate whether there is empirical support that implementing the ISTE Standards for Students can result in learning gains. A scoping review methodology was used to map extant literature to evidence of learning gains. To ensure transparency in the selection of the articles and the evidence gathering procedure, an a priori method was used. This study is unique in that it provides the first examination of a set of student standards for technology use to learning gains within …

Join The Sons Of Liberty! Exploring 1773 Bloxels Boston, Elisa Shaffer

STEMPS Faculty Publications

Learners will create a colonial character to explore 1773 Boston and gain insight into the underpinnings of the events that led up to and occurred during the Boston Tea Party on December 16, 1773. Using Bloxels, learners will travel the streets of Boston, interacting with different characters and learning about their concerns and events. They will also interact with British soldiers and tax collectors. Additionally, they will be given an opportunity to join the Sons of Liberty and participate in the Boston Tea Party.

Exploring Instructional Designers' Utilization And Perspectives On Generative Ai Tools: A Mixed Methods Study, Tian Luo, Pauline S. Muljana, Xinyue Ren, Dara Young

STEMPS Faculty Publications

The emergence of generative artificial intelligence (GenAI) has caused significant disruptions on a global scale in various workplace settings, including the field of instructional design (ID). Given the paucity of research investigating the impact of GenAI on ID work, we conducted a mixed methods study to understand instructional designers (IDs)’ perceptions and experiences of utilizing GenAI across a spectrum of ID tasks. A total of 70 IDs completed an online survey, and 13 of them participated in the semi-structured interviews. The survey results indicated IDs’ familiarity with and perceived usability of GenAI tools in performing various ID responsibilities in their …

Investigating Division Quest: A Text-Based Adventure Narrative Game For Overcoming Difficulties Of Mitosis Learning, Amanda G. Conner

College of Graduate Studies: Theses & Dissertations

Mitosis learning is a source of struggle for many introductory biology students. Much of this difficulty stems from an overwhelming amount of terminology and moving pieces as well as the abstract nature of cellular processes. Game-based learning (GBL) has been used in other contexts to reduce cognitive load and provide relatable experiences upon which students can construct their mental models. However, commercial GBL is often expensive and difficult to align with individual instructor teaching preferences and learning objectives. In this study, we use a mixed methods approach to explore the use of a GBL tool made in Twine to overcome …

Utilizing Internet Memes In Senior High School Biology To Improve Gen Z’S Academic Achievement, Attitude, And Self-Efficacy, Alyanna Nicole Carlos, Emmanuel D. Delocado

Biology Faculty Publications

Generation Z learners’ short attention span challenges educators to design engaging teaching methods that capture their interest. This quantitative study investigates the effect of memes, which are popular internet media, on non-STEM Gen Z high school students’ academic achievement, attitude, and self-efficacy in biology. Two groups of Grade 11 participants (n=243) were taught cellular division and genetics lessons through two different approaches. The results demonstrate that the experimental group which was taught using meme-infused materials had statistically significantly higher post-test scores (21.46 ± 4.41 out of 30; independent t-test = 0.00) than students who were taught with materials with no …

A Multi-Stakeholder Perspective On Online University Education Adoption In Nigeria, David Seyi Akanbi

Graduate Research Theses & Dissertations

The demand for university education exceeds the supply in Nigeria, as more than 70% of eligible applicants cannot get admission into Nigerian universities annually. With a current population of 206 million, the World Bank predicts the Nigerian population will surpass the United States to become the third-largest country in the world by 2050. If the current university system cannot meet the demand of the current population, the gap may continue to widen even in the future. Although universities in other countries have adopted online learning to help meet the demand for university education, Nigerian universities’ administrators and regulators are reluctant …