Usefulness of Instructor Annotations on Flipped Learning Preparation Video System

Flipped learning is a method that flips in/out class activities to make lectures learner-centered. In flipped learning, comments from learners on preparation material are useful information for instructors to consider before deciding in-class topics. Thus, we arrive at the notion that receiving comments from instructors will be effective for learners watching the video. By including annotations from instructors, we propose to improve the quality of content for learners and thus enhance learners' motivation and study satisfaction. To achieve this, we introduced "Steering Mark," a tool that enables learners to easily grasp the overall structure of a video, to the video learning system. We examined the effectiveness and influence of Steering Mark through an experiment with 34 undergraduate learners. As a result, Steering Mark was found to be useful in improving the quality of video content for learners.Comment: The 2019 International Conference on Advanced Informatics: Concepts, Theory and Application

A Tool to Support Students-to-Teacher Feedback in Asynchronous Online Contexts

In recent years, the world of education has become increasingly Hybrid (online / on location) and Flexible (synchronous / asynchronous). One of the risks of these mixed environments is the distance between teacher and students that can make interaction, a crucial component of the teaching / learning process, more difficult. This paper introduces Evoli, a tool to support the “HyFlex model”; more specifically, the component dealing with online / asynchronous mode. Evoli enables teachers to receive precise, time-stamped feedback by their students on educational materials (typically videos). Students go through the materials and express their level of understanding as well as their questions and comments. Dashboards with the students' data allow the teacher to know, topic by topic, what is clear and what is not and thus how to organize the synchronous sessions. The tool was evaluated in a real-life setting, involving 63 graduate students in a course on Plasma Physics. The students filled in a System Usability Scale questionnaire and some questions regarding the perceived usefulness of the tool; the teacher's opinion was gathered via a semi-structured interview. Results show that students found the tool both usable and useful; the teacher's opinion was that the tool allowed prompting more reactions than a normal setting and an optimization of teaching organization

Video Creation Tools for Language Learning: Lessons Learned

Video creation tools—from Skype to PowerPoint to iMovie—have become increasingly popular conduits for foreign language teaching and learning. In flipped-classroom and blended-learning models, video enables faculty to move routine language concepts (i.e., grammar and vocabulary) outside the classroom, leaving more in-class time for live engagement with teacher and classmates. This chapter discusses lessons learned and new data collected at the University of Pennsylvania Libraries’ Weigle Information Commons on video’s effectiveness in various language learning contexts. Data collected includes reflections on several years of course observations, interviews with language faculty members, and a campus-wide survey to gauge student perspectives on video’s role in the language learning experience. Themes that have emerged include the range of video tools available to perform a given task, perceptions of tool usefulness and ease of use (depending on faculty and student technology comfort levels), and the role of the library as a central resource for technology support and course integration. Our study contributes to the scholarly conversation by providing a taxonomy of current tools used, their efficacy in our context as a measure for other contexts, and skills recommended by faculty and staff for effective incorporation of video tools in the language classroom

Large Language Model-based System to Provide Immediate Feedback to Students in Flipped Classroom Preparation Learning

This paper proposes a system that uses large language models to provide immediate feedback to students in flipped classroom preparation learning. This study aimed to solve challenges in the flipped classroom model, such as ensuring that students are emotionally engaged and motivated to learn. Students often have questions about the content of lecture videos in the preparation of flipped classrooms, but it is difficult for teachers to answer them immediately. The proposed system was developed using the ChatGPT API on a video-watching support system for preparation learning that is being used in real practice. Answers from ChatGPT often do not align with the context of the student's question. Therefore, this paper also proposes a method to align the answer with the context. This paper also proposes a method to collect the teacher's answers to the students' questions and use them as additional guides for the students. This paper discusses the design and implementation of the proposed system.Comment: 6 page

Towards Student Engagement Analytics: Applying Machine Learning to Student Posts in Online Lecture Videos

The use of online learning environments in higher education is becoming ever more prevalent with the inception of MOOCs (Massive Open Online Courses) and the increase in online and flipped courses at universities. Although the online systems used to deliver course content make education more accessible, students often express frustration with the lack of assistance during online lecture videos. Instructors express concern that students are not engaging with the course material in online environments, and rely on affordances within these systems to figure out what students are doing. With many online learning environments storing log data about students usage of these systems, research into learning analytics, the measurement, collection, analysis, and reporting data about learning and their contexts, can help inform instructors about student learning in the online context. This thesis aims to lay the groundwork for learning analytics that provide instructors high-level student engagement data in online learning environments. Recent research has shown that instructors using these systems are concerned about their lack of awareness about student engagement, and educational psychology has shown that engagement is necessary for student success. Specifically, this thesis explores the feasibility of applying machine learning to categorize student posts by their level of engagement. These engagement categories are derived from the ICAP framework, which categorizes overt student behaviors into four tiers of engagement: Interactive, Constructive, Active, and Passive. Contributions include showing what natural language features are most indicative of engagement, exploring whether this machine learning method can be generalized to many courses, and using previous research to develop mockups of what analytics using data from this machine learning method might look like

Proceedings of the 1st Annual Higher Education Flipped Learning Conference

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Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course

Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may provide insights into student learning performance and inform the improvement of video-assisted teaching tactics. Nevertheless, video analytics are not accessible to learning stakeholders, such as researchers and educators, mainly because online video platforms do not broadly share the interactions of the users with their systems. For this purpose, we have designed an open-access video analytics system for use in a video-assisted course. In this paper, we present a longitudinal study, which provides valuable insights through the lens of the collected video analytics. In particular, we found that there is a relationship between video navigation (repeated views) and the level of cognition/thinking required for a specific video segment. Our results indicated that learning performance progress was slightly improved and stabilized after the third week of the video-assisted course. We also found that attitudes regarding easiness, usability, usefulness, and acceptance of this type of course remained at the same levels throughout the course. Finally, we triangulate analytics from diverse sources, discuss them, and provide the lessons learned for further development and refinement of video-assisted courses and practices

The potential benefits of using videos in higher education

The developments of digital technology have opened new outlooks for online education which offer students the flexibility to learn at any time and any place. With all this instructional changes instructors, in all levels of the educational chain have been compelled to adapt quickly to this reality. They have a wide diversity of tools available to grab student’s attention and motivate them to embrace the knowledge in their own learning process. One of these resources is the use of videos. Through them lecturers can deliver complex information and contents to students and, if used creatively, videos can become a powerful technological tool in education. In this article we will explore some of the potential benefits and challenges associated with the use of videos in the teaching and learning process at higher education levels. We will also discuss some thoughts and examples for the use of teaching materials to enhance student’s learning and try to change ideas about the potentialities and future of video’s annotation new software resources, as incoming open tools for group work involvement

Exploring tablet PC lectures: lecturer experiences and student perceptions in biomedicine

Lecturers using tablet PCs with specialised pens can utilise real-time changes in lecture delivery via digital inking. We investigated student perceptions and lecturer experiences of tablet PC lectures in large-enrolment biomedicine subjects. Lecturers used PowerPoint or Classroom Presenter software for lecture preparation and in-lecture pen-based inking. Using surveys and lecturer interviews, students and lecturers were asked to reflect on their tablet PC lectures in comparison to non-tablet lectures that used prepared images and a laser pointer. Quantitative survey responses suggested that students felt that the tablet lectures were more interesting, that they were more capable of keeping up with the lecturer, and they enhanced their understanding of the lecture content. Qualitative analysis of written comments indicated that students appreciated the real-time writing and drawings, particularly because these were visible on lecture recordings. When reflecting on their non-tablet lectures, most lecturers used the pen-based writing, drawing and highlighting tablet functions and reduced lecture pace and content for their tablet lectures. Long-term tablet use led to lecturers making more use of digital inking, with less use of prepared images. Our results support the idea that tablet PC-supported lectures are conducive to improved management of cognitive load via reduced lecture pace and content