Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors’ routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner–instructor interaction (inter alia, communication, support, and presence) has a profound impact on students’ satisfaction and learning outcomes. Thus, identifying how students and instructors perceive the impact of AI systems on their interaction is important to identify any gaps, challenges, or barriers preventing AI systems from achieving their intended potential and risking the safety of these interactions. To address this need for forward-looking decisions, we used Speed Dating with storyboards to analyze the authentic voices of 12 students and 11 instructors on diverse use cases of possible AI systems in online learning. Findings show that participants envision adopting AI systems in online learning can enable personalized learner–instructor interaction at scale but at the risk of violating social boundaries. Although AI systems have been positively recognized for improving the quantity and quality of communication, for providing just-in-time, personalized support for large-scale settings, and for improving the feeling of connection, there were concerns about responsibility, agency, and surveillance issues. These findings have implications for the design of AI systems to ensure explainability, human-in-the-loop, and careful data collection and presentation. Overall, contributions of this study include the design of AI system storyboards which are technically feasible and positively support learner–instructor interaction, capturing students’ and instructors’ concerns of AI systems through Speed Dating, and suggesting practical implications for maximizing the positive impact of AI systems while minimizing the negative ones.

/pdf/the-impact-of-artificial-intelligence-on-learner-instructor-1q3ic64po0.pdf

The impact of artificial intelligence on learner-instructor interaction in online learning.

Given the importance of student engagement for students' current and future success, it is essential to explore how teachers can foster student engagement within lessons. This study relied on classroom observations to describe how teachers applied Self-Determination Theory (SDT) related (de)motivating teaching behaviours to foster students' engagement. Results from 120 observed lessons of 43 teachers indicated there were distinct relations between motivating teaching behaviours and student engagement. Most striking regarding the use of motivating teaching behaviours were the higher levels of relatedness support and guidance during activities in lessons in which students showed the highest levels of engagement. Conversely, in lessons where students were least engaged, teachers showed higher levels of chaotic teaching behaviours. Analyses of behaviours within lowly and highly engaging lessons showed that teachers in highly engaging lessons were observed to start with high levels of enthusiasm and after about ten to fifteen minutes focused on activating their students by offering room for experimenting and support while students worked on assignments. In contrast, teachers in lowly engaging lessons seemed to have a tendency to employ demotivating teaching behaviour at the start of the lesson. Implications and directions for future research are discussed.

https://www.tandfonline.com/doi/pdf/10.1080/02671522.2020.1767184

Fostering student engagement with motivating teaching: an observation study of teacher and student behaviours

As a result of the frustration with the dominant “What Works” paradigm of large-scale research-based improvement, practitioners, researchers, foundations, and policymakers are increasingly embracin...

Research on Continuous Improvement: Exploring the Complexities of Managing Educational Change.

Globally, many schools are replacing traditional classrooms with innovative flexible learning spaces to improve academic outcomes. Little is known about the effect on classroom behaviour. Students from nine secondary schools (n = 60, M age = 13.2±1.0y) were observed via momentary time sampling for a 30 minute period, in both a traditionally furnished and arranged classroom and a flexible learning space containing a variety of furniture options to accommodate different pedagogical approaches and learning styles. The teaching approaches in both conditions were documented. In traditional classrooms the approach was predominantly teacher-led and in the flexible learning space it was student-centred. Students in flexible learning spaces spent significantly more time in large group settings (d = 0.61, p = 0.001), collaborating (d = 1.33, p = 0.001), interacting with peers (d = 0.88, p = 0.001) and actively engaged (d = 0.50, p = 0.001) than students in traditional classrooms. Students also spent significantly less class time being taught in a whole class setting (d = -0.65, p = 0.001), engaged in teacher-led instruction (d = -0.75, p = 0.001), working individually (d = -0.79, p = 0.001), verbally off-task (d = -0.44, p = 0.016), and using technology (d = -0.26, p = 0.022) than in traditional classrooms. The results suggest that the varied, adaptable nature of flexible learning spaces coupled with the use of student-centred pedagogies, facilitated a higher proportion of class time interacting, collaborating and engaging with the lesson content. This may translate into beneficial learning outcomes in the long-term.

https://ro.uow.edu.au/cgi/viewcontent.cgi?article=5672&context=sspapers

Flexible learning spaces facilitate interaction, collaboration and behavioural engagement in secondary school.

Social isolation is one of the most common consequences of older people with dementia, especially for those who live at their own dwellings alone due to limited access to social activities. Research relating to the use of social robots in aged care has increasing attention to facilitating the support to care services for older people with dementia. Particularly less attention has focused on the applicability of social robots in home care services. This paper aims to study the engagement and robot experience of older people with dementia while interacting with a social robot named Betty in the context of home-based care. This paper contributes to the research relating to care service embedded robots by expanding the knowledge regarding longitudinal research in home based care, while there is limited long-term study in this context. The results show that social robots are evident to be able to engage with older people with dementia at home. Consequently, designing social robots in a social context is desirable. While the robots enabled service for the human partner within the social context is possible, there is a need to underpin the concept of personhood to realize personalization of services and its contents to suit individual preferences.

Engagement and experience of older people with socially assistive robots in home care.

Recent theoretical conceptualizations of student engagement have raised questions about how to measure student engagement and how engagement varies not only across schools, but also within school and within classrooms. The authors build on existing research on student behavioral engagement and extend this research to emphasize a continuum of disengagement, active engagement, and passive engagement. They review common approaches to measuring engagement and highlight areas where new theoretical conceptualizations of engagement require new approaches to measurement. The authors analyze how student behavioral engagement changed depending on the context and demonstrate the need of a finer scale of engagement. They find there was not a uniform association of higher behavioral engagement and student interaction with peers, but it was the interaction with other students and the teacher that was predictive of increased engagement. Their work suggests that disaggregating behavioral engagement into disengage...

Understanding student behavioral engagement: Importance of student interaction with peers and teachers

This paper presents evidence from a unique reform model that allowed teachers and other educators in a large urban district to collaborate with one another in the development of an innovation meant to improve student ownership and responsibility. In this longitudinal case study, we describe school stakeholders’ learning about the design, the process of knowledge-transfer to school teams, and how school teams shared their ongoing learning with one another. School implementation teams were initially reluctant to share their learning with one another. By engaging in a shared innovation development process with structures for routine sharing, over time, implementation team members were increasingly interested in sharing their learning with one another. We discuss the implications for school improvement efforts.

/pdf/system-learning-in-an-urban-school-district-a-case-study-of-1l73nbeqrt.pdf

System Learning in an Urban School District: A Case Study of Intra-District Learning.

/pdf/understanding-student-behavioral-engagement-importance-of-7xbfgvs7zs.pdf

Understanding Student Behavioral Engagement: Importance of Student Interaction with Peers and Teachers.

System learning in an urban school district: A case study of intra-district learning

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Understanding student behavioral engagement: Importance of student interaction with peers and teachers

System Learning in an Urban School District: A Case Study of Intra-District Learning.

Understanding Student Behavioral Engagement: Importance of Student Interaction with Peers and Teachers.

System learning in an urban school district: A case study of intra-district learning