In early 2020, the COVID-19 pandemic led to a rapid shift to emergency remote teaching and mandatory digital learning in higher education. This study tested an extended causal model built on the Unified Theory of Acceptance and Use of Technology (UTAUT) under the restrictions on higher education stemming from the pandemic. Data collected from a survey among 485 students were analyzed using structural equation modeling. Confirmatory factor analyses were performed to examine the construct validity of the measurement model using polychoric correlations. Path analysis was used to test the causal model. The results indicate a psychologically sound baseline model with nine latent variables that affect students’ behavioral intention to accept and continue using technology for learning. However, the model is only partially in line with the proposed causal model based on UTAUT. The implications of these results are discussed in terms of technology acceptance and use in higher education, both under the restrictions leading to mandatory digital learning and in future.

In accordance with this precept, several scholars, such as Merrill (1994), Reigeluth (1993, 1999), Tennyson and Elmore (1997) and many others, have focused on theories of instructional design. However, a more detailed analysis reveals the observation that these authors do not describe theories of instructional design in a narrow sense but rather theories on learning and how instruction could operate on them (e.g., Tennyson, 2010).

Higher education appears to be a popular field of participatory instructional design and rapid prototyping. Since decades, manifold efforts have been invested at universities and colleges to improve instruction and learning. These efforts have been made in particular to meet the needs of the stakeholders, i.e., the students attending institutions of higher education for the purpose of acquiring key competences.

From the very beginning, instructional design has been strongly influenced by information technology so that the label instructional technology sometimes became a synonym.

Up to now, instructional design has been described as a science of planning (Leshin, Pollock, & Reigeluth, 1992; Schott, 1991) that contains both a theory and technology of planning.

The goal of this chapter is to provide a theoretical background for the understanding of the various aspects of model-based simulations and their infusion in instructional fields of application. Therefore the potential of computer simulation to enhance student learning and problem-solving, defined as a change in a student's mental model, is described. Mental models, conceptual models and simulations are distinguished. Further-on modeling technologies are discussed with regard to glass-box and black-box models. A crucial question is how instructional design can integrate simulation technologies and the evoked cognitive processes into instructional planning. The chapter closes with perspectives for future development.

This chapter discusses how the approach of mental models can be applied to Instructional Design (ID) and eventually leads to a theoretical concept of model-centered Instructional Design. The various critiques of Instructional Design which describe ID as too fixed, slow and which doubt that there is room for ID in the Information Society, will serve as the starting point for the discussion. This contribution takes up these critical views and opens up a look at ID from a model-centered perspective. The argumentation starts out with a reference to the underlying epistemological foundations and is based on the fundamental understanding of human cognition as the construction of mental models when confronted with more or less complex challenges. Further-on the application of the concept of mental models to learning and Instruction is the "building block" to ID. Thus ID is understood as a higher-order process of model construction. Thereby the approach of mental models can lead to a new perspective on Instructional Design, which can successfully defend against the critiques of Information Technologists. However, Model-Centered Instructional Design may help to see existing excellent layouts of ISD products from another perspective, which helps to understand the mystery of the human learning processes more precisely than other can do. The question if this leads to a paradigm shift in Educational Science hasn't been answered yet.

Important educational implications have been drawn mainly from two movements in epistemology: constructivism and situated cognition. Whereas constructivism is relevant for instruction primarily on a meta-theoretical level, the concept of situated cognition has strong educational implications for instructional practice. A central assumption of situated cognition is that people construct mental models to meet the requirements of (learning) situations to be cognitively mastered. Research on how to influence the construction of mental models has been criticized by several authors from a theoretical and methodological perspective. This chapter asks: Has descriptive research on mental models in instructional contexts provided results that can serve as a foundation for prescriptions to facilitate or improve the student’s construction of mental models? We first discuss the characteristics of learning situations that necessitate the construction of mental models. Our next step is a search for theoretically sound conceptions of instruction that either impel students to construct mental models for themselves or which adaptively guide and direct the students in the process of model construction. We report on an exploratory study which investigated: (a) the applicability of cognitive apprenticeship for designing effective learning environments; (b) the effect of providing an initial conceptual model on learner construction of mental models during instruction; and, (c) the long-term effectiveness of a multimedia learning program on acquired domain-specific knowledge and the stability of initially constructed mental models. Finally, we address what happens when there are no relevant learner preconceptions available.

This textbook on Instructional Design for Learning is a must for all education and teaching students and specialists. It provides a comprehensive overview about the theoretical foundations of the various models of Instructional Design and Technology from its very beginning to the most recent approaches. It elaborates Instructional Design (ID) as a science of educational planning. The book expands on this general understanding of ID and presents an up-to-date perspective on the theories and models for the creation of detailed and precise blueprints for effective instruction. It integrates different theoretical aspects and practical approaches, such as conceptual ID models, technology-based ID, and research-based ID. In doing so, this book takes a multi-perspective view on the questions that are central for professional ID: How to analyze the relevant characteristics of the learner and the environment? How to create precise goals and adequate instruments of assessment? How to design classroom and technology-supported learning environments? How to ensure effective teaching and learning by employing formative and summative evaluation? Furthermore, this book presents empirical findings on the processes that enable effective instructional designing. Finally, this book demonstrates two different fields of application by addressing ID for teaching and learning at secondary schools and colleges, as well as for higher education.