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.