How Learning Technologies Are Studied and Used at the Doctoral Level

Learning technologies change quickly, but doctoral study goes beyond mastering emerging platforms. It prepares professionals to critically investigate how technologies influence learning, performance, and organizational outcomes. Through theory, research, and evidence-based inquiry, doctoral researchers examine not only whether a technology works, but also why it works, for whom, and under what conditions. 

Professionals entering doctoral study may bring experience from education, business, healthcare, corporate training, technology, or other organizational settings. Doctoral research builds upon that experience by helping professionals investigate complex challenges, evaluate technology-supported solutions, and contribute new knowledge to their fields. 

What Nobody Tells You About Studying Learning Technologies at the Doctoral Level 

Professionals entering doctoral study may already know how to select or implement instructional tools. The larger challenge is learning to examine those choices systematically and question assumptions that once seemed obvious. 

That shift means looking for evidence rather than adopting a tool because it is new. Adaptive learning technology in education may adjust instruction for an individual learner, but researchers still need to determine whether the adaptation serves the intended academic goal. 

This perspective reframes another familiar question: “How does education technology improve the teaching and learning processes?” At the doctoral level, the answer begins with a clear theory and an appropriate research design. Evidence from the setting then shows whether the technology fulfills its purpose. 

The Difference Between Using Learning Technology and Studying It 

Using a learning platform requires practical knowledge of how it functions. Studying a learning technology involves examining its design, implementation, use, and outcomes through systematic research. Researchers investigate how the technology functions, how people interact with it, and what evidence demonstrates its effectiveness. 

This distinction becomes especially important as schools adopt AI and other emerging tools. Keiser University has explored the impact of AI on education. Doctoral researchers extend that conversation by asking how a tool affects particular learners under specific instructional conditions. 

The Theory-Practice Gap in Educational Technology 

Learning technology sits at the intersection of research and professional practice. A technology may appear to solve an immediate learning or performance challenge without revealing why it worked or whether similar results would occur in another setting. Doctoral study provides professionals with the theoretical knowledge and research skills needed to investigate those questions systematically and apply findings to future decisions. 

What It Means to Become a Scholarly Practitioner in This Field

A scholarly practitioner uses research to examine problems encountered in professional practice. Evidence can challenge the assumptions behind an existing approach and guide the practitioner’s next decision. 

Keiser’s overview of the instructional design process offers a practical look at how training is developed. Doctoral study adds the research fluency needed to investigate why one design choice may support learners more effectively than another. 

The Theoretical Frameworks That Shape Learning Technology Research 

Technology alone does not provide a sufficient basis for doctoral research. Researchers also need a theoretical framework that explains what they expect to observe and how the results should be interpreted. 

Learning Theory as the Foundation for Technology Evaluation: Behaviorism, Cognitivism, Constructivism and Beyond 

Learning theory gives researchers a basis for explaining how learning is expected to occur. A behaviorist lens focuses on observable responses, while constructivism considers how learners build understanding through experience. Cognitive theory draws attention to the mental processes involved in memory and information processing. 

Because each framework defines learning differently, the choice of theory can shape both the research question and the technology being evaluated. 

The Institute of Education Sciences has supported education technology research involving artificial intelligence and intelligent tutors. Rather than judging these tools only by their classroom functionality, doctoral researchers can use theory to examine how adaptive feedback is expected to support learning. 

Connectivism, Heutagogy and the Learning Theories That Technology Has Not Yet Caught Up With 

Digital learning has encouraged researchers to consider theories built around networks and learner independence. Connectivism treats connections as part of how knowledge develops. Heutagogy places greater emphasis on learners directing their own educational process. 

Both perspectives can inform adult learning, where prior experience often shapes how a learner approaches new material. Greater independence may also affect which technologies feel useful or restrictive. 

How Theoretical Frameworks Function as Research Lenses, Not Just Literature Review Requirements 

A theoretical framework influences what researchers treat as evidence. It also guides the interpretation of findings that might otherwise appear ambiguous. 

Research indexed by ERIC considers the relationship between theory and learning analytics in multimodal analytics research. The work illustrates why researchers need to define what counts as learning before deciding how to measure it. 

The Research Methodologies That Define Learning Technology Scholarship 

The research method should follow the question rather than the technology. In this field, a strong design also accounts for the setting in which an intervention is used. 

Design-Based Research: The Methodology That Belongs to This Field 

Design-based research (DBR) is one approach used to develop, study, and refine learning interventions in authentic settings. Researchers examine how a design functions in practice, collect evidence, and use findings to inform subsequent improvements. This iterative approach can be valuable when investigating learning technologies in educational, workplace, and organizational environments. Depending on the research question, doctoral researchers may also use qualitative, quantitative, or mixed-methods approaches. 

Mixed Methods, Learning Analytics and the Shift Toward Data-Rich Doctoral Research 

Digital systems can produce extensive numerical data, but numbers do not always explain the learner’s experience. Mixed-methods research connects measurable patterns with qualitative evidence that can help researchers understand why those patterns appeared. 

Learning analytics can be useful because digital systems record many aspects of learner behavior. The doctoral challenge is deciding which data points address the research question and which information merely adds volume. 

Usability Research, User Experience Design, and Human Factors 

Effective learning technologies must be both functional and accessible to the people who use them. Doctoral researchers may examine usability, user experience, accessibility, and human interaction to better understand how technology supports or limits learning and performance. These considerations are relevant across educational institutions, workplaces, healthcare organizations, and other professional settings. 

The Ethics of Learning Technologies in Doctoral Research 

Educational technology can collect learner data and use it to generate automated recommendations. Doctoral researchers must therefore consider privacy as part of the research design. They also need to preserve meaningful human agency. 

Learning Analytics, Surveillance and the Line Between Insight and Intrusion 

A digital system may record when a learner logs in and how that person moves through content. Assessment performance creates another data source. These records can support research, but clear rules must govern how the data is collected and protected. 

Algorithmic Bias in Adaptive Learning Systems: A Research Problem, Not Just a Technical One 

Adaptive systems can create customized learning paths, but personalization does not guarantee an equitable or effective result. Researchers might compare how recommendations function across learner groups and settings. An unexpected pattern may point to bias in the data or design. 

The Commercialization of Education Technology and Researcher Independence 

Educational technology research operates alongside a large commercial market. Scholarly independence requires researchers to separate vendor claims from demonstrated educational results. 

Artificial Intelligence Is Rewriting the Learning Technology Research Agenda 

Artificial intelligence has intensified questions that already existed in educational technology research. Researchers still need to determine what changes and who benefits. The conditions surrounding those results matter just as much. 

In 2024, the Institute of Education Sciences funded four research and development centers focused on generative AI in teaching and learning. Their work includes exploratory classroom studies intended to understand how AI is being used in practice. 

How Doctoral Students Are Using AI as a Research Tool: What the Field Is Still Figuring Out 

Doctoral students may use AI to support parts of the research process while also studying AI as an educational intervention. In either role, the researcher remains responsible for verifying the work. 

Keiser has also examined future trends in distance education, where emerging technologies continue to shape how instruction is delivered. Delivery methods may change, but researchers still need to evaluate whether those changes help students understand and apply what they learn. 

AI as a Research Subject: Questions Doctoral Researchers Can Examine 

Doctoral researchers may investigate how artificial intelligence influences learning, decision-making, professional practice, and organizational performance. Research questions might examine whether AI improves learning outcomes, supports employee development, enhances accessibility, changes in professional workflows, or introduces ethical and operational challenges. Researchers can also explore how individuals interact with AI and the conditions under which its use produce meaningful results. 

The Unanswered Questions That Make This an Open Research Field 

An open field gives doctoral researchers room to make a contribution. Strong studies define precisely what AI changes and identify the conditions under which that change matters. 

From Practitioner to Researcher: The Professional Identity Shift Doctoral Study Requires 

Professionals entering doctoral study bring valuable knowledge from their respective fields, including education, business, healthcare, technology, organizational leadership, and workforce development. Doctoral study helps them transform observations from professional practice into meaningful research questions, investigate complex problems systematically, and contribute knowledge that can inform future practice and organizational decision-making. 

Keiser’s discussion of instructional design careers across different industries illustrates the range of settings in which professionals may build experience. Doctoral study offers a way to extend that background through advanced research. 

The Identity Shift Nobody Prepares You For 

The transition to becoming a scholarly practitioner involves treating a professional concern as a researchable problem. A platform that appears successful becomes the subject of a more disciplined question about evidence. 

Professional Experience Strengthens Research Questions 

Professionals who work directly with learners may notice problems that a casual observer misses. Doctoral methodology provides a systematic way to investigate those problems. 

Doctoral Study Opens New Professional Directions 

Advanced doctoral preparation may support professional growth in instructional design leadership, learning and development, organizational research, technology strategy, consulting, and other roles that require advanced research and analytical expertise. These skills can help professionals contribute to innovation, evaluate organizational initiatives, and lead evidence-informed change across industries. 

Choosing the Right Advanced Degree in Learning Technology 

Prospective students should examine the purpose and curriculum of each credential rather than treating all post-master’s programs as interchangeable. 

Keiser University’s EdS and PhD in Instructional Design and Technology 

Keiser Graduate School offers an Education Specialist in Instructional Design and Technology as well as a PhD in Instructional Design and Technology.  

These programs provide opportunities for professionals from diverse backgrounds to deepen their understanding of learning technologies, instructional design, and their applications across professional settings. 

The EdS emphasizes advanced professional preparation, while the PhD places greater emphasis on original research and scholarship. Professionals considering either pathway should evaluate their academic interests, professional goals, and desired level of engagement with research when selecting a program.. 

From EdS to PhD: Building an Intentional Academic Pathway

The EdS may appeal to professionals seeking advanced specialization, while the PhD moves further into original research and scholarship. Students should compare both curricula with their goals before choosing a path. 

Advance Your Career With Keiser University Graduate School 

Keiser University Graduate School offers advanced education programs at the master’s, specialist and doctoral levels, including: 

• Master’s: Education Leadership, MSEd L or Education, Teaching and Learning, MSEd TL
• Education Specialist: Educational Leadership, EdS or Instructional Design and Technology, EdS
• Doctoral: EdD in Curriculum Leadership, Curriculum and Instruction, PhD, Doctor of Education – Education Leadership, EdD, Educational Leadership, PhD or Instructional Design and Technology, PhD

With nearly 50 years of academic excellence, Keiser University offers a long-established setting for advanced study. Visit our graduate school page or connect with our graduate admissions counselors to learn more.

Contributing Authors: Dr. Jessica Fuda Daddio