Summer 2025 

• EDCI 52800 - Human Performance Technology (3 credits, online)

  • This course offers an introduction to Human Performance Technology (HPT), covering fundamental concepts and principles related to human performance. It explores the theoretical foundations, research, and practical applications within the field, along with different methods for addressing human performance challenges. The course emphasizes a systematic process for analyzing, designing, developing, implementing, and evaluating interventions aimed at improving performance in organizational settings. Its main objective is to equip students with the essential knowledge and skills needed to begin a professional career in performance technology.

• EDCI 56400 -  Integration and Management of Technology for Learning (3 credits, online)

  • This course is designed for teachers, trainers, administrators, and others who currently use or plan to use computers in instructional settings. It focuses on techniques and challenges related to integrating computers into educational environments. Topics explored include the theoretical foundations of technology integration, teaching and learning issues associated with using technology, the design of educational applications for classroom use, and emerging research and practical issues in technology integration.  

Spring 2025 

• EDCI 67400 - Advanced Instructional Design Theories (3 credits, face-to-face)

  • This course focuses on various instructional-design theories and their applications. During the initial weeks of the course, you will examine and discuss background information from a wide variety of cognitively based perspectives. You will participate in discussions targeted on the key/guiding principles of these selected theories. In the latter portion of the semester, our focus will shift somewhat to the application and evaluation of the theories within various real-world projects, situations, and cases.

• EDPS 55700 -  Intro to Quantitative Data Analysis Methods in Education II (3 credits, face-to-face)

  • This course is specially designed to enhance students' quantitative reasoning and skills through discussions of issues in educational data and authentic data analysis experiences of a variety of education data. The topics to be covered in this course include simple/multiple linear regression, different types of group comparison methods (including n-way ANOVA, ANCOVA, repeated-measures ANOVA, and mixed ANOVA). The course is specifically designed: 1) to understand how the quantitative methods covered in the course can be used appropriately to address proposed research questions in education, and 2) to interpret quantitative results meaningfully for a given context.  

• EDCI 59000 - AI in STEM Inquiry (3 credits, online)

  • This course is designed to provide opportunities for STEM educators to develop understanding of teaching and learning with AI Applications. Central to this work is the construction of models of learners’ understanding of AI as an “assistant” and of the user as the analyst of the assistant’s products. Educators’ models of learners’ perspectives on their role and the role of AI in the production of knowledge is central in curricular reasoning. While curricular efforts have historically focused on the development of learner concepts and knowledge application, the AI era requires a shift in attention to learner analysis of machine generated information and graphics. In the AI era, educators seek to build insights about the reliability of information and associated knowledge as well as techniques for analyzing information and graphics that lead to new knowledge of learners’ understanding and problem-solving strategies. In this course we will develop models of learner’s understandings of different facets of AI applications and then use those models and our emerging understanding of curriculum in our disciplines to explore challenges in teaching and learning with AI. We will discuss how teachers and students can engage to support the emergence of powerful strategies and mental structures that can be applied to generate new understandings in interaction with STEM disciplines.

Fall 2024 

• EDCI 59100 - From Consumer to Creator: Understanding AI Education and Integrating it into Teaching (3 credits, online)

  • This course aims to provide students with the knowledge and skills needed to understand and utilize Generative AI in education. Students will acquire fundamental coding skills and develop technical expertise in using and comprehending AI. By engaging in hands-on activities and analyzing real-world case studies, students will design and create their own AI applications using Google Teachable Machine to solve a specific problem of their choosing. Additionally, the course will examine ethical issues related to AI/GenAI, allowing students to establish guidelines for the meaningful integration of AI/GenAI in teaching and learning.

• EDPS 53300 - Introduction to Educational Research I: Methodology (3 credits, face-to-face)

  • The purpose of this course is to provide students with a conceptual understanding of the basic concepts and procedures in educational research. Students will learn to read and evaluate research and plan an empirical study. The emphasis of the course is on the methodology and evaluation of educational research and will require a minimum of computational skills. The fundamental research principles are applicable to other fields of study as well. No prerequisite courses are required. 

• EDCI 67700 - Unpacking Research: Writing a Research Proposal (2 credits, face-to-face)

  • This course is designed to introduce the novice researcher and learner to the process of writing a research proposal on topics relevant to the field of Learning Design and Technology. Emphasis is placed on helping the learner to understand how to get started with the proposal writing process, working through the process in full in order to apply it to their own personal research agenda, and eventually the dissertation process. 

• EDCI 61500 - Introduction to Qualitative Research (3 credits, face-to-face)

  • This course is an introduction to the foundations and landscape of qualitative inquiry. During the semester, we will examine how your beliefs shape your understanding of research and explore the deeper epistemological concerns associated with research that help us create, claim, and justify our claims to knowledge. We will also explore the various ways of dealing with procedural, philosophical, analytical, and ethical issues related to undertaking qualitative research projects. We will learn and practice various methods and approaches used in qualitative research design and explore how qualitative research can be used in education, and across disciplinary fields such as STEM, anthropology, and sociology, to name a few.

Summer 2024 

• EDPS 55600 - Introduction to Quantitative Data Analysis Methods in Education I (3 credits, online)

  • This course is designed to provide an overview of introductory quantitative data analysis methods in education. The course is specially designed to enhance students’ quantitative reasoning and skills through discussions of issues in educational data and authentic data analysis experiences of a variety of education data. The topics to be covered in this course include data collection and description, sampling distributions, and methods of quantitative data analysis often used in education research. 

• EDCI 62100 - Technology for Qualitative Research (3 credits, online)

  • This course is exploration of the effective use of technology to facilitate data collection, organization, and analysis. Emphasis on application of theoretically-based methodologies for handling and analyzing qualitative data through the use of qualitative data research software (QDAS). Course also includes attention to other digital tools relevant to the collection, organization and analysis of qualitative data. Most effective for graduate students who have completed a qualitative methodology course and who have already begun the collection of qualitative research data. 

Spring 2024 

• EDCI 53100 - Learning Theories And Instructional Design  (3 credits, hybrid)

  • This course has been designed to help you learn how theories of human learning and motivation can be applied to the instructional process in order to make the process more effective, efficient, and/or appealing. The focus of the course is on two areas: 1) the theoretical principles that have contributed to the field of Instructional Design (ID), and 2) how those principles can be applied within practical settings. 

• EDCI 56900A - Introduction To E-Learning (3 credits, face-to-face)

  • This course examines how the design and development of instruction are impacted by the use of the computer as delivery system. A primary focus is on effective learning design strategies for e-learning. Learners will identify and apply effective design practices with emphasis on project management, planning, and implementation. Education or training materials will be developed using appropriate authoring tools as determined by the instructional context. Learners will design an E-Learning module with end-to-end documentation of the design process (Project Plan, Design Document, Storyboard). Opportunities for collaborative feedback and evaluation will also be featured elements of the course experience. 

• EDCI 63800 - Curriculum And Instruction Doctoral Seminar II (1 credit, hybrid)

  • This course consists of an examination of current educational research. EDCI and other faculty will present and lead discussions of their research. Students will be exposed to research within multiple paradigms and perspectives. This course is intended for all new doctoral students in the Department of Curriculum and Instruction and should be taken within the first year to doctoral study. 

• EDCI 67600 - Unpacking Research: Writing Literature Reviews In Learning Design And Technology (1 credit, hybrid)

  • This course is designed to introduce the learner to the process of analyzing and preparing literature reviews on topics relevant to the field of Learning Design and Technology. Emphasis is placed on helping the learner to understand, critique, and synthesize the research literature in order to apply it to their own personal research agenda. Course activities and assignments are designed to help the learner develop the knowledge, tools, and strategies needed to become thoughtful consumers and producers of research and to use this knowledge to inform their practice. Learning experiences revolve around two major themes: 1) the examination and thoughtful critique of current research and 2) preparation of a thorough literature review that provides a rationale for continued study.