Abstract
Teachers play a crucial role as end-users of technology in educational settings but seldom get recognition as a group of technology users with varying needs and perspectives. This paper analyzes the unique user characteristics of teachers, both in terms of general user nature and within the context of established ed-tech frameworks and technology acceptance models. The authors argue that existing frameworks and models inadequately address the distinct characteristics of teachers as users and therefore provide specific recommendations for the development of a specialized framework that accounts for the teacher’s specific user criteria.
Keywords
Introduction
In recent decades, the quality of education has been transformed by many technological innovations. Still, the question remains whether these innovations empower teachers and students with more knowledge and autonomy or rather lead them to lose control over information while creating a technology dependency (UNESCO, 2023). While this disparity between system and human efficiency in educational technology affects all stakeholders, teachers arguably encounter the most significant challenges. To enhance learning with technology, teachers must meet ed-tech standards, follow institutional policy, and balance their needs with those of their students. The rise of Generative Artificial Intelligence (Gen-AI) adds a new layer to this expectation. Now teachers need to rethink their role in the presence of an AI actor, distinguish between human and AI-generated content, and consider the broader societal implications of this changing learning paradigm.
Even though teachers’ roles as users evolve with technological advancements, there are not many studies that focus specifically on their unique user profile. The paper aims to critically examine the role of teachers as a unique group of users and explore the characteristics that shape their adoption, implementation, and sustained use of technology. Two questions are addressed throughout this paper:
Teachers as Users in Ed-tech: A Stakeholder Perspective
Effective technology integration begins with recognizing the diverse needs and behaviors of the users within the system. Unfortunately, often the perception of who a teacher is and what they do does not align with the teacher’s actual user experience. The design and development of ed-tech products depends on developers who view the internet as the new and personalized learning space, replacing traditional classrooms. So, teachers’ roles are incomplete without constantly guiding students online as opposed to teaching in schools alone (Ideland, 2021). In reality, this vision adds to the workload of teachers with rigid curriculums, teaching, and grading. On the other hand, the tech implementation is predicted and led by school administrators, department heads, or instructional designers, leaving teachers out of the decision-making process. This, in turn, leads teachers to become skeptical of the tools and hesitate to fully incorporate them in classrooms (Reeves et al., 2023). Additionally, ed-tech consultants try to balance these visions of tech implementation with actual experience, but administrative compliance and commercial interests oversimplify complex pedagogical issues and further reduce teacher autonomy (Joecks, 2024). As a result, even the most cutting-edge technology fails to aid teachers with simple tasks. For example, AI-based pairing for large classes sounds convenient, but it is a labor-intensive process for teachers. They must enter all student data, monitor matches, and review feedback instead of creating groups by themselves. (Yang et al., 2021). Therefore, even for the most helpful learning product to reach its full potential in design and application, a comprehensive understanding of the user characteristics of teachers is necessary.
Attributes of Teachers as Users
In human-computer interaction (HCI), a typical user profile includes information about demographics, such as age, gender, educational background, culture, skill, training, experience, goal, and personality (Kujala & Kauppinen, 2004). While these attributes provide the groundwork for a teacher persona, their evolving role as tech users shapes their identity. The following section shows the different roles teachers play as users in tech integration.
User Autonomy
User behavior is influenced by the length, frequency, and responsibility for their use (Liu et al., 2010). In the context of teachers and technology, these factors are significant as their influence on technology use and product choices demonstrate their user behavior. Regardless of their age, gender, or experience, teacher autonomy in choosing and controlling the method, duration, and impact of teaching determines their attitude toward technology and decides their role as active or passive users (Serin & Bozdag, 2020).
Type of Interaction
Users have different levels of interactions, including instructional, conversational, manipulative, exploratory, and responsive styles (Lueg et al., 2019; Preece et al., 1994). Analyzing these traits for teachers can inform the ed-tech design process. For instance, some teachers may only use technology to deliver instruction, while others may engage in conversations with chatbots, experiment with digital tools, or explore virtual and physical spaces to discover new information.
User as Designer
User actions involve many stages: establishing the goal, making a plan, specifying the action, executing the action, becoming aware of impacts, making sense of it, and evaluating it (Norman, 2013). Breaking down the teaching practice into these tasks reveals the extensive amount of work teachers actually do. They set goals by combining their needs, student needs, and institutional regulation. Based on these factors, teachers plan lessons, specify actions for themselves and students for each session, perform the task in the class, interpret the actions taken, and finally evaluate their outcome.
Cognitive-Emotional Behavior
The emotional responses of teachers to physical objects or experiences are also an important part of their user behavior. So, teachers’ response to technology might be predicted by understanding the three layers of human emotions: visceral (how it looks), behavioral (how it works), and reflective (how it aligns with our goals) ((Norman, 2013; Choi & Kim, 2016). Analyzing a teacher’s reaction to a tool’s esthetic appeal, usability, and applicability for their teaching philosophies and institutional objectives will be helpful in measuring the likelihood of their acceptance and implementation of ed-tech innovations.
Adopter Personality
Another approach to user-centered design is Rogers’s (2003) five adopter categories, which classify users based on their enthusiasm for innovation and involvement. According to this, teachers may be categorized as innovators, early adopters, early majority, late majority, and laggards, depending on their interest in embracing new tech tools and integrating them into practice. Some teachers are curious about using new tools. Others may accept the conventional uses of technology and feel comfortable about passively following instructions.
This section demonstrates one of many ways to identify unique characteristics of teachers as users by placing them in the broad user frame and identifying the criteria needed for a teacher-centered approach to ed-tech design.
Teachers as Users in Theories and Frameworks
Educational technology frameworks and user acceptance models are widely used to understand teachers’ needs and experiences as well as to guide them in integrating technology. However, the extent to which these frameworks adequately address their user characteristics needs to be carefully considered. This section examines a range of popular models and frameworks in ed-tech contexts and their representation of teachers.
Technology Acceptance Model (TAM)
According to the technology acceptance model (TAM) model, the perceived usefulness (PU) and perceived ease of use (PEU) influence teachers’ intention to use technology, which, in turn, influences their actual use (Venkatesh & Bala, 2008). This model has been adapted with additional variables to better accommodate diverse user contexts. For instance, when assessing teacher acceptance of a specific technology like ChatGPT, factors related to the tool need to be added, including its quality in content design, perceived enjoyment, and self-efficacy of users (Dehghani & Mashhadi, 2024). Moreover, teachers’ responses to TAM surveys or questionnaires are influenced by their considerations of students as end-users of technology. They value the usefulness of technology for students over personal convenience. Thus, the motivation, beliefs, and challenges of teachers are not fully captured by the TAM model (Frøsig, 2023).
Unified Theory of Acceptance and Use of Technology (UTAUT)
According to UTAUT, four key factors influence behavioral intention and use: performance expectancy, effort expectancy, social influence, and facilitating conditions. These factors are moderated by individual differences like gender, age, experience, and voluntariness of use (Venkatesh et al., 2003). These moderating constructs are generic and not always suitable for measuring the complexities of teachers’ user behavior, leading to a misleading representation of their perception in studies. For example, facilitating conditions are important to only early-career teachers, while mid-career teachers care more about community influence. Teachers want IT proficiency more than the voluntariness of use and autonomy. Teachers prioritize performance, not effort, and workload, because their ultimate goal is a sense of accomplishment (El Alfy & Kehal, 2024; Kim & Lee, 2022; Zhang & Wareewanich, 2024). Adding teacher-specific attributes like self-efficacy, prior tech experience, and teaching style even deteriorates the model’s ability to predict teachers’ user behavior (Kahnbach et al., 2024).
Technological Pedagogical Content Knowledge (TRACK)
The TPACK model identifies four technology-related knowledge areas essential for teachers inside the larger area of contextual knowledge, outlining the specific tech skills for each one (Mishra & Koehler, 2006). To achieve technological knowledge (TK), teachers need to be expert users, capable of using technology to complete various tasks. For Technological content knowledge (TCK), they must be innovative to transform the content in their discipline with technology and vice versa. For technological pedagogical knowledge (TPK), they should surpass the traditional uses of technologies and exhibit creativity in using digital tools. Ultimately, they need to combine all aspects of knowledge and expertise to have TPACK. Although this framework is ideal in theory, it is not very user centric. It creates a dilemma for teachers about choosing between basic tech proficiency and advanced tech expertise. Besides, the personal aspects of their knowledge, particularly individual beliefs, cultural knowledge, backgrounds, and interpersonal relationships, are fundamental for meaningful knowledge construction, but they are not addressed in TPACK (Haga, 2024; Schmid et al., 2024).
SAMR (Substitution, Augmentation, Modification, and Redefinition)
According to the SAMR framework, effective technology integration depends on the user’s level of expertise in technology adoption (Puentedura, 2013). To substitute tech for traditional teaching tools, teachers need basic tech skills. For augmentation, they need to enhance learning with technology. Educators with higher skills become more integrative, redesigning tasks and activities for modification and even creating entirely new learning experiences for redefining learning with technology. However, the teaching context is overlooked here, such as the availability of tech tools, the need for tech integration or levels of integration in courses, the usefulness of different levels of implementation, the non-linear progression of tech users, and differences between the digital proficiency of teachers and students. In addition, without a clear standard for technology integration, teachers develop biases and strive for the highest level of this hierarchical framework as proof of successful tech implementation, create their own interpretation of the levels, and view new technologies as transformative and familiar technologies as merely enhancing learning (Hamilton et al., 2016; Nguyen, 2024).
Discussion and Future Directions
As users of technology, teachers keep evolving as they explore technology applications in educational settings, leading to a dynamic shift in their user behaviors. So, the user journey must be examined, taking into account teachers’ unique user qualities, such as explorers, followers, and early adopters, which influence their usage patterns and contexts. However, existing ed-tech frameworks and technology acceptance models often create unrealistic expectations of teachers in terms of user expertise, overlooking the nuances in their journey, and presenting a distorted profile of teachers as users. The “how” and “why” of ed-tech adoption are emphasized over the “who”- the teacher’s distinct needs, experiences, and perspectives.
To effectively measure the characteristics of teachers as users, future frameworks and theories must consider the following key aspects:
Enhancing teacher digital fluency, tailored to individual and professional settings, is crucial for effective technology integration. This has practical implications for providing teachers with personalized training and support, leading to more engaging learning experiences. From a research perspective, a standardized framework for teachers as technology users is needed to inform educational research, engineering research, and UX design, investigating teachers’ technological needs and experiences to develop effective training programs and educational tools.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.