The power of feedback.

A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Multimedia in Learning

Arthur Chickering is Distinguished Professor of Higher Education at Memphis State University. On leave from the Directorship of the Center for the Study of Higher Education at Memphis State, he is Visiting Professor at George Mason University. Zelda Gamson is a sociologist who holds appointments at the John W. McCormack Institute of Public Affairs at the University of Massachusetts-Boston and in the Center for the Study of Higher and Postsecondary Education at the University of Michigan.

Seven Principles for Good Practice in Undergraduate Education: Faculty Inventory. Institutional Inventory.

This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning dashboards are becoming popular due to the increased use of educational technologies, such as Learning Management Systems (LMS) and Massive Open Online Courses (MOOCs). The initial search of five main academic databases and GScholar resulted in 346 papers out of which 55 papers were included in the final analysis. Our review distinguishes different kinds of research studies as well as various aspects of learning dashboards and their maturity regarding evaluation. As the research field is still relatively young, most studies are exploratory and proof-of-concept. The review concludes by offering a definition for learning dashboards and by outlining open issues and future lines of work in the area of learning dashboards. There is a need for longitudinal research in authentic settings and studies that systematically compare different dashboard designs.

Perceiving Learning at a Glance: A Systematic Literature Review of Learning Dashboard Research

It has come to our attention that Dr Herb Thompson, professor of Economics and Chair of the Economics department, devotes his first assignment to discovering exactly that. He asks his students to fill an on-line questionnaire on Learning Styles and to hand him the results of this questionnaire. We have asked him to write a piece on “learning styles” for our New Chalk Talk series. We have also asked him to share the results of the questionnaires which he has conducted over two semesters in his Microeconomics class. Dr Thompson has agreed to do this and for that we thank him very much. New Chalk Talk will devote the next two or three issues to this subject. They will appear starting next Tuesday.

Learning and Teaching Styles

Technology acceptance has become a key concept for the successful rollout of technical devices. Though the concept is intensively studied for nearly 20 years now, still, many open questions remain. This especially applies to technology acceptance of older users, which are known to be very sensitive to suboptimal interfaces and show considerable reservations towards the usage of new technology. Mobile small screen technology increasingly penetrates health care and medical applications. This study investigates impacts of aging, technology expertise and domain knowledge on user interaction using the example of diabetes. For this purpose user effectiveness and efficiency have been measured on a simulated small screen device and related to user characteristics, showing that age and technology expertise have a big impact on usability of the device. Furthermore, impacts of user characteristics and success during the trial on acceptance of the device were surveyed and analyzed.

Effects of Aging and Domain Knowledge on Usability in Small Screen Devices for Diabetes Patients

Mathematics students, often among large university classes of several hundreds of students, are easily daunted when solving math problems. Lacking individual feedback, they easily give up. To bolster learning, Computer-Aided Assessment may help students by giving them individual feedback about their progress. This article presents some general requirements for Intelligent Assessment using semi-automatic feedback in mathematics education with a special focus on solution processes. Intelligent Assessment implies the combination of human assessment along with electronic assessment via intelligent software for evaluating a student’s performance in a specific subject. Assessment tools are used to categorize solutions and detect errors as accurately as possible. Unusual and novel solutions and errors that the computer cannot categorize are forwarded to a tutor or teacher for assessment. Several examples demonstrate that semi-automatic and process-oriented Intelligent Assessment can help to improve learning and, ultimately, student self-confidence in mastering problems.

E-Learning Tools with Intelligent Assessment and Feedback for Mathematics Study

The use of computer-based mathematics tools is widespread in learning. Depending on the way that these tools assess the learner's solution paths, one can distinguish between automatic assessment tools and semi-automatic assessment tools. Automatic assessment tools directly provide all feedback necessary to the learners, while semi-automatic assessment tools involve the teachers as part the assessment process. They are provided with as much information as possible on the learners' interactions with the tool. 
How can the teachers know how the learning tools were used and which intermediate steps led to a solution? How can the teachers respond to a learner's question that arises while using a computer tool? Little is available to answer this beyond interacting directly with the computer and performing a few manipulations to understand the tools' state. 
This paper presents SMALA, a web-based logging architecture that addresses these problems by recording, analyzing and representing user actions. While respecting the learner's privacy, the SMALA architecture supports the teachers by offering fine-grained representations of the learners' activities as well as overviews of the progress of a classroom.

Understanding the Learners' Actions when using Mathematics Learning Tools

Mobile small screen technology increasingly penetrates health care and medical applications. However, usability research regarding the ease of using these devices, as well as acceptance issues did mostly address aspects of IC-Technologies in younger and healthy users. This study investigates impacts of ageing and domain knowledge on user interaction using the example of diabetes. First, the software for the monitoring of diabetes had been developed and implemented on a PC. The simulated diabetes assistant was displayed on a small screen device as well as on a very large display, simulating an ambient assisted living environment. In a second step, the navigation behavior of younger and older diabetes patients as well as healthy users was assessed. Results show that age and display-size have a big impact on the device interaction, independently of domain knowledge. Furthermore, it was found that simple usage of a bigger screen could be helpful for tutoring patients in using a mobile electronic living assistant.

Task performance in mobile and ambient interfaces. Does size matter for usability of electronic diabetes assistants

Mobile small screen technology increasingly penetrates health care and medical applications. However, usability research regarding the ease of using these devices, as well as acceptance issues did mostly address aspects of IC-Technologies in younger and healthy users. This study investigates impacts of ageing, technological expertise and domain knowledge on user interaction using the example of diabetes. First, the software for the monitoring of diabetes had been developed and implemented on a PC. The simulated diabetes assistant was displayed on a small screen device as well as on a very large display, simulating an ambient assisted living environment. In a second step, the navigation behavior of younger and older diabetes patients as well as healthy users was assessed. Results show that age and display-size have a big impact on the device interaction, independently of domain knowledge. Furthermore, it was found that simple usage of a bigger screen could be helpful for tutoring patients in using a mobile electronic living assistant. In order to assess usability of the device acceptance was measured after the experiment and was found to be positivley correlated with effectiveness.

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Daniel Herding

Papers

Effects of Aging and Domain Knowledge on Usability in Small Screen Devices for Diabetes Patients

E-Learning Tools with Intelligent Assessment and Feedback for Mathematics Study

Understanding the Learners' Actions when using Mathematics Learning Tools

Task performance in mobile and ambient interfaces. Does size matter for usability of electronic diabetes assistants

Mobile Devices Used for Medical Applications: Insights Won from a Usability Study with Diabetes Patients