Learner engagement in digital or online learning has been identified as one of the many challenges and personalizing the digital learning content to keep students motivated and engaged throughout the duration of course is gaining much interest among academia. The purpose of this study is to identify the levels of student engagement and understand the relationship between learner engagement and their academic performance. This study has used k-means machine learning algorithm to identify the levels of student's engagement and tried to identify the relationship between the engagement metrics and student performance using correlation analysis. Based on students’ engagement metrics, k-mean algorithm classifies students in to two levels, namely High engaged students, and Low engaged students. The results of correlation analysis showed that there was a positive correlation between the engagement metrics and performance. Identifying the levels of student engagement possibly will help in personalizing the learning by recommending the e-content based on engagement metrics and identifying the relationship between the engagement metrics and performance might help faculty to design activities and content for the courses.

There has been a growing call to nurture and prepare current engineering graduates to think and act ethically as the products designed by engineers have both individual and societal implications. Engineering ethics revolves around the professional obligation of engineers to society, their employers, and the profession. Engineering codes of ethics commonly referred to as fundamental cannons form the base for engineering ethics education. It focuses on micro ethical issues, fundamental overarching responsibility to protect human health, welfare, and the environment or promote sustainable development. Engineering ethics was introduced to first-year engineering students as part of a PBL based course, which was taught in a blended mode due to the disruptions caused by the COVID19 pandemic. This study attempts to assess students’ knowledge of engineering ethics and their ability to identify and resolve ethical dilemmas by applying the fundamental canons. When a module like engineering ethics was introduced to the first-year engineering students in a blended mode, it was essential to identify methods that would help assess students’ understanding of engineering ethics. Students learn the concepts of engineering ethics through asynchronous videos. The module’s primary objective was to develop students’ ability to identify and resolve ethical dilemmas and map fundamental cannon. A discussion forum was set up, allotting students with a case study that had an ethical dilemma used as an instrument to assess the students. The results discuss mainly the cognitive levels that the students have reached in resolving an ethical dilemma. The analysis also predicted the areas where students found it challenging to understand the concepts.

The world has witnessed an unprecedented disruption due to the COVID-19 pandemic, temporarily halting various educational activities at educational institutes like universities, schools and colleges. Both educators and learners were forced to adapt to the new situation and continue to face the challenges, together. Hence many universities and colleges were compelled to move from the traditional method of teaching to the online method of delivering courses. Blended learning has been adopted to effectively deliver the courses online which comprises asynchronous and synchronous delivery. KLE Technological University turned this situation into an opportunity of beginning a new era of learning on campus, there was a strategic shift from traditional learning to blended learning. In this blended model, the student learned various courses in asynchronous mode through pre-recorded videos and study material on the Learning Management System (LMS). When the students learn in such an online learning environment, there comes a demand for learning accountability, hence there was a need to implement best assessment practices during asynchronous learning. The assessment method chosen was post-test, which was conducted to assess if the students had met their learning goals. This paper mainly focuses on conducting the post-test effectively and carrying out an extensive analysis of the student’s performance. To make sure students have understood the concepts well, the questions framed were of higher bloom’s level focusing on the different topic learning outcomes. An intervention was designed to create concept-wise questions mapped to bloom’s level and different outcome-based education parameters. Post-test results are collected using a tool called Dipstick integrated with the LMS. Through this tool different reports are generated that helps the course instructor to analyze the student’s depth of learning. The graphs generated through the Dipstick tool shows dips wherever a student lacks in understanding the concepts. The Dipstick report will help the course instructor in identifying and convincing the unclear concepts to the students by thinking in two dimensions, that of re-designing the content or by thinking of effective pedagogy to teach the concepts.

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.