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The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional practice related to such lectures. This paper introduces Tcherly, a teacher-facing dashboard that presents class-level aggregated time series data on students' self-reported cognitive-affective states they experienced during a lecture. Instructors can use the dashboard to evaluate and improve their instructional practice related to video lectures. We report the detailed iterative prototyping design process of the Tcherly Dashboard involving two stakeholders (instructors and designers) that informed various design decisions of the dashboard, and also provide usability and usefulness data. We demonstrate, with real-life examples of Tcherly Dashboard use generated by the researchers based on data collected from six courses and 11 lectures, how the dashboard can assist instructors in understanding their students' learning experiences and evaluating the associated instructional materials.

Student and teacher perceptions of course content are critical components of the teaching and learning process. Studies that have investigated such perceptions offer conflicting evidence of both convergence and divergence between the perceptions of students and teacher. These studies used data modalities such as interviews and surveys, which have different granularities of information in them. We analysed student and teacher perceptions of difficulty in a mechanical engineering lecture with multiple data modalities capable of capturing perceptions at different granularities. Our analysis revealed a multiscale nature of perceptions, wherein the students' and their teacher's perceptions can appear to both converge and diverge depending on the scale of interpretation, which is a function of the modality and granularity of data used in the study. At macroscale, the students and the teacher agreed about difficult sections of the lecture and the underlying reasons. However, their reasoning diverged when probed at finer scales. Furthermore, we note that convergence observed between the perceptions of the teacher and students at a coarse scale can sometimes hide differences in finer scale perceptions. We discuss the implications of these results for the interpretation of results from past studies and for practitioners.