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This chapter discusses a bottom-up design strategy to support the principles of Universal Design and Universal Design for Learning adapted for online course development. The concept of Universal Design demands a holistic, bottom-up instructional design model for online course development that integrates technology, accessibility, recent instructional and learning theories, and a participatory postmodern worldview. This study is intended for faculty, instructional designers, administrators, assistive technology staff, and Web multimedia software vendors associated with higher education. The research assists these target audiences to design and develop online courses that are accessible without special adaptation or modification. The components of Universal Design for online learning support newer emergent approaches to instructional design, various programming solutions used in the software engineering field for efficiency, Universal Design for Learning, and legal guidelines associated with accessibility.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

English teacher candidates have limited opportunities to examine classroom-based discussions about LGBTQ-themed texts and heteronormativity in teacher education courses. This chapter presents one effort to address this issue using a video-based field experience in the English Methods course that demonstrated a critical unit of instruction about the play, Angels in America. The chapter provides a description of the project and English teacher candidates’ perspectives about what they learned for English educators interested in devising similar projects for their courses.

Web-enhanced instruction is increasingly pervasive in higher education. Homework assignments and exams are increasingly completed online. Instructors evaluate the effectiveness of educational tools, such as web-based homework (WBH), in part through student performance that can be affected by students’ motivation. Thus, changes in students’ motivations and perceptions during an academic term can affect our assessment of the efficacy of the educational tool depending on when our assessment is conducted. No current studies identify variations in student perceptions of educational technology over time. Better understanding the changes in student perceptions of educational technology as they complete a course of study may help educators develop more effective instructional and pedagogical strategies. Our study explores how students’ attitudes toward WBH change with use.

Teaching Net Generation accounting students is a challenging experience. They anticipate that technology will be an integral part of the teaching–learning processes that we offer them. This chapter focuses on how to use technology tools to create innovative course materials, delivery methods, and collaborative processes.

The chapter explains how I combined traditional instructional methods and technology-mediated learning (TML) techniques to create a practice–feedback–interaction process for use with two undergraduate auditing courses. I taught the first course (Auditing) during Fall Quarter 2006 and the second course (Advanced Auditing) during Winter Quarter 2007. I taught both courses in a blended instructional format.

This chapter shows how I used the practice–feedback–interaction process with individual and team writing assignments in the two auditing courses. I explain how the TML process works and describe technology tools used at each step of the process. Student comments provide feedback about how they reacted to using the technology-mediated teaching–learning process.