In this work, we propose a framework for integrating the information from behavioral and cognitive spaces to perform attention profiling of a learner while engaging with digital content. Attention profiling helps examine and comprehend students' concentration, attention, and cognitive engagement patterns. Attention profiling of learners enables educators to discern the digital content types that effectively engage students, identify potential distractors, empower educators to customize learning resources and enhance students' overall learning experience. Attention profiling integrated into the Learning Management System (LMS) environment helps students by providing feedback on the content or resources that require more focus. Several studies focus on student engagement through behavioral cues, including click stream data, time spent watching the videos, number of GIT commits, and participation in discussion forums; however, limited research is available in measuring student attention using both behavior cues and cognitive measurements. We address the problem of attention profiling of a learner using the data from behavioral and cognitive spaces. Integrating the data from both spaces necessitates a fusion technique to enhance the performance of the attention profiling of a learner. We propose to use EEG and eye gaze information from cognitive and behavioral space, respectively. We used 'Stroop test,' 'Sustained Attention to Response Task’ (SART), and 'Continuous Performance Task’ (CPT) to invoke selective attention and sustained attention states among learners. The data collected during the mentioned tests served as ground truth. Further students watched three different types of videos and we collected the data from cognitive space using Emotiv+, a 14- channel head mount EEG device, and the data from the behavioral space through eye gaze information using a web camera-based solution. The advantage of the Emotiv+ device is the comprehensive coverage of sensors across both brain hemispheres, and the device’s real-time data stream includes raw EEG and FFT/band power. On the other hand, to capture the on-screen and offscreen behavior of the learners, we used the L2CS-Net gaze estimation architecture built on ResNet-50. We aim to develop a coordinated multimodal data representation framework by employing co-learning methods.

The Work-in-progress paper discusses the faculty development model. The workplace problems for engineers in the 21st century demands interdisciplinary skills. To cater to the need, the educators need to make interventions for inculcating interdisciplinary skills among students. The challenge is that very limited focus is on preparing the faculty towards building interdisciplinary knowledge, skills and mentoring capabilities. The authors through this paper share an experience of deploying a faculty training model used for training the faculty towards mentoring interdisciplinary projects. The presented faculty development model is a result of the heuristic experience of four iterations and is organically evolved. The model was implemented in the context of a first-year engineering course titled Engineering Exploration. The course uses PBL pedagogy and every faculty, mentors a set of students to complete an interdisciplinary project. The nature of the projects in the course demands knowledge and skills from different domains to be applied at the mentioned stages. To mentor such interdisciplinary projects, faculty needs to be formally trained. However, in the literature authors found very limited architecture in the direction of standard frameworks and models that can be used to train the faculty towards interdisciplinary thinking and mentoring. The paper describes the evolved faculty training model consisting of four following phases where initial phases are focused on improving the technical skills among faculty members while the latter phase is focused on improving the mentoring skills.

This work-in-progress paper documents the transition of an undergraduate engineering university from in-person, lecture-based instruction to a blended model. The proposed work describes the planning, training, technology deployment, review, and monitoring of the blended learning model. In this process, the faculty were empowered to create content, practice studio etiquettes, edit videos, upload content to a streaming server, and create the courses in Learning Management System (LMS). The qualitative evaluation of this initiative was conducted from a pedagogical perspective using the research question: What challenges are faced by faculty members while transitioning from in-person learning to blended learning in undergraduate engineering education? Thematic analysis of the transcribed data revealed that challenges could be categorized as technical, pedagogical, multiple demanding roles, and nature of courses which further open up opportunities for evidence-based interventions.

This paper focuses on the experience of design and implementation of a virtual exhibition for exhibiting the artifacts of the project done by first-year students in a design-based and Project-Based Learning course in engineering education. The authors present the advantages and challenges faced during the design and implementation of the virtual exhibition and compare it with the physical exhibition through qualitative analysis of faculty perceptions about physical and virtual exhibitions. This paper intends to help engineering educators through a set of guidelines that help them design and implement virtual exhibitions.