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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.

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.

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.

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