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The purpose of this study was to examine the relationship between factors in the extended technology acceptance model (TAM) model and teachers' self-efficacy in remote teaching during the COVID-19 pandemic. In addition, the authors sought to listen to classroom teachers as they expressed their unbiased views of the advantages, disadvantages and challenges of teaching remotely during the COVID-19 pandemic.

A survey was employed to examine the relationship between factors in the extended TAM model and teachers' self-efficacy in remote teaching during the COVID-19 pandemic using the 49-item questionnaire. A multiple regression analysis using a stepwise procedure was used to examine the relationship between factors in the extended TAM model and teachers' self-efficacy. Three open-ended questions closely examined remote teaching during the pandemic, related to challenges, advantages and disadvantages.

Qualitative findings challenges included Internet connection, lack of interaction and communication and challenges with motivation and student engagement. Disadvantages included teachers’ level of self-efficacy in using technology to teach, lack of support and resources to teach online and the struggle to motivate and engage students. Perceived benefits included flexibility for the teacher and differentiation, rich resources and a way to support learners when in-person instruction is not possible.

The data suggest that instead, during COVID-19, many teachers were learning about the platforms simultaneously as they were instructing students.

To ensure quality remote instruction and that students receive the support to make instruction equitable, teachers need to perceive that their instructional technology needs are met to focus on teaching, learning and needs of their students.

Teachers need opportunities to explore the platforms and to experience success in this environment before they are exposed to the high stakes of preparing students to meet K-12 standards.

Instructional delivery has not explored teacher motivational and instructional teaching self-efficacy related to satisfaction with the learning management system (LMS).

Pew and Mavor (1998) called for an integrative representation of human behavior for use in models of individual combatants and organizations. Models with integrated representation of behavior have only been achieved at rudimentary levels according to those performing the studies (e.g. Pew & Mavor, 1998; Tulving, 2002) and those building the models (e.g. Warwick et al., 2002). This chapter will address aspects of cognitive performance that are important to incorporate into models of combat based on acceptance of theory, strength of empirical data, or for other reasons such as to bridge gaps where incomplete knowledge exists about cognitive behavior and performance. As a starting point, this chapter will assess which of Pew and Mavor’s recommendations are still appropriate as determined by a review of selected literature on cognition and its representation. We will also provide some review and extensions of key literature on cognition and modeling and suggest a way ahead to close the remaining gaps. Different aspects of cognition are described with recent findings, and most are followed by an example of how they have been represented in computer models or a discussion of challenges to their representation in modeling.

The smart city strategies of municipalities in South Africa have been grounded in developmentalism, seeking to harness the power of technology to enable improved governance. Cities such as Durban and Cape Town have embraced infrastructure-led approaches that seek to use state-mediated broadband “backbone” development to enable last-mile ICT access to marginalized communities. With the advent of big data, the range of actors in the ICT-local government terrain has broadened to include partnerships with IT-multinationals and management consultants to streamline municipal bureaucratic procedures, enable data processing, and contribute to greater efficiency. An important driver is the increasingly urgent need to accelerate the delivery of essential services while also encouraging investment and development through greater efficacy (e.g., in processing development applications). A “dashboard urbanism” is becoming evident that fits well with the system of indicators and performance monitoring that is embedded in the managerial South Africa’s local government system. The danger of an overreliance on these quantitative aspects is that it may perpetuate divides in what is considered to be one of the most unequal cities in the world. Based on exploratory research, this chapter explores strategies used by civil society organizations to challenge the assumptions of “dashboard urbanism” and contribute a more rounded appropriation of big data and a deepened and contextualized urban experience.