The potential of learning analytics (LA) to improve learning and teaching is high. Yet, the adoption of LA across countries still remains low. One reason behind this is that the LA services often do not adequately meet the expectations and needs of their key stakeholders, namely students and teachers. Presently, there is limited research focusing on the examination of the students’ expectations of LA across countries, especially in the Nordic, largely highly digitalized context. To fill this gap, this study examines Swedish students’ attitudes of LA in a higher education institution. To do so, the validated survey instrument, Student Expectations of Learning Analytics Questionnaire (SELAQ) has been used. Through the application of SELAQ, the students’ ideal and predicted expectations of the LA service and their expectations regarding privacy and ethics were examined. Data were collected in spring 2021. 132 students participated in the study. The results show that the students have higher ideal expectations of LA compared to the predicted ones, especially in regards to privacy and ethics. Also, the findings illustrate that the respondents have low expectations in areas related to the instructor feedback, based on the analytics results. Further, the results demonstrate that the students have high expectations on the part of the university in matters concerning privacy and ethics. In sum, the results from the study can be used as a basis for implementing LA in the selected context.

This Innovate Practice work-in-progress paper presents findings around how distance learning, due to the the COVID-19 pandemic, affected students as measured by time-on-task in programming.In this qualitative study, we examine a group of 36 second year upper-secondary students in Programming 1 during a nine week period in Spring 2021. During this time, they alternated between one whole week of distance learning followed by two weeks of in school instruction. For the Programming 1 lessons, students used an online platform to write, edit and run code in. We analyzed the log data from the platform to estimate time-on-task for each student for every lesson both at home and at school.We observed that students were affected differently by distance learning as measured by time-on-task. 12 students had more average time-on-task at school. 15 students had more average time-on-task at home. Nine students had less than five minutes difference on average.In addition to the analysis of time-on-task, students were given a survey in Fall 2021 to follow up on their experiences with in-school teaching and distance learning. In the survey, students were asked questions about their study environment at home during distance learning. From the responses, 13 students described their study environment as “in bed” despite having access to a table and chair in a room for themselves and twenty-three students described their study environment as “playing video games during online lectures”. Not surprisingly, students that said they were playing video games during online lectures had a lower average time-on-task by about ten minutes than their peers. Interestingly, students that said they participated in class in bed had a higher average time-on-task by about ten minutes than their peers.Correlating responses from the survey and time-on-task data, we reason about how students’ study environments at home affected their time-on-task and how distance learning has affected students in the pandemic.

Assessment plays an important role in education and can both guide and motivate learning. Assessment can, however, be carried out with different aims: providing the students with feedback that supports the learning (formative assessment) and judging to which degree the students have fulfilled the intended learning outcomes (summative assessment). In this study, we explore the instructors’ perspective on assessment within the context of introductory programming courses offered to non-computer-science majors at a public tuition-free state-funded university in a Nordic country. These courses are given to a large number of students and also employ several teaching assistants (TAs). We used constructivism as a basis for our study and investigated how instructors implement formative and summative assessments, how they view their role, and what expectations they have of their TAs in these assessments. We interviewed seven course coordinators (main instructors for introductory programming courses with additional administrative duties but without formal responsibility of the grading) and analyzed 205 course artifacts, such as syllabi, lab assignment instructions, and course material from the cross-department TA training course. The results showed that course coordinators use formative and summative assessments both separately and within the same activity. They view themselves as responsible for the assessments, as the planners and material developers, as the organizers and administrators, and as monitors of the assessments. However, the results also showed that these course coordinators delegate much of the responsibility for the assessments to their TAs and expect TAs to both grade the students and provide them with feedback and guidance. In addition, the TAs are also expected to act as informants about their students’ performance. The course coordinators’ role entails many different aspects, where communicating through instructions to both students and TAs is essential. We see that this implementation of assessment, with lots of responsibility distributed to the TAs, could be difficult to manage for a single faculty member who is not necessarily responsible for the grading. Based on the results, we outline some recommendations, such as offering TA training.

Many online learning initiatives have failed to reach beyond the environments in which they were first developed. One exception is the Open Learning Initiative (OLI) at Carnegie Mellon University (CMU). In an attempt to validate the question-based learning methodology implemented in OLI, we developed online material for an introductory course in object-oriented programming, and tested it on two course offerings with a total of 70 students. As our course has been given in the same format for several years, we also had comparable assessment data for two classes prior to our intervention in order to determine that we did not introduce any obvious harm with this methodology. Findings show a reduced teaching and learning time by 25%. No statistically significant differences could be found in the results of the assessment quizzes nor confidence surveys completed by the students. The two teachers (the same who handled the classes before the intervention) took different paths to teaching preparations with this new methodology. One teacher increased preparations, whilst the other reduced them, but both teachers were convinced that using online question-based learning was superior to the previous lecture and textbook-based approach, both for the students and themselves in terms of overall satisfaction. We also gathered time logs from the development to estimate return on investment.

Programme Integrating Courses (PICs) aim to tie students, teachers and courses in education programmes closer together. In this study, we investigate three PICs, as part of engineering programmes in computer science and media technology. The purpose of this study was to gain a deeper understanding of how students and mentors experience the PICs with a focus on the assessment and the relationship between students, and students and mentors. We used a mixed method approach, interviewed 22 students and 6 mentors, and sent out questionnaires to all 25 mentors and all students from two of the three courses (630+470 students). The results showed that the students and mentors appreciated the social aspects of the courses, getting to know each other and share experiences. However, some were uncomfortable reflecting upon the given non-technical topics. On a general level, the students stated that their mentors assessed their reflections correctly but they were sceptical towards being graded on a scale other than pass/fail.

Student engagement is crucial for successful self-paced learning. Feeling isolated during self-paced learning with neither adequate supervision nor intervention by teachers may cause negative emotions such as anxiety. Such emotions may in turn significantly weaken students' motivation to engage in learning activities. In this paper, we develop a self-pacedlearning environment (FishBuddy) that aims to reduce anxiety and promote student engagement. We construct and implement a physiologically-state-aware performance-evaluation model for identifying potentially fruitful moments of intervention when students show frustration during learning activities using an Apple Watch application that measures heart rate and alerts the student to watch a visualization of his or her own physiological state. We have conducted an experiment with 20 first-year undergraduate students, randomly separated into an experimental group and a control group, who carry out online, self-paced English grammar exercises. The students in the experimental group used FishBuddy and those in the control group did not. The self-reports from both groups show that FishBuddy significantly reduced reported experiences of anxiety and isolation in the experiment. Further to this, students who used FishBuddy were engaged longer with the exercises. The average scores on the exercises between the two groups, however, were not significantly different.

We present a method for audio-visual classification of Swedish phonemes, to be used in computer-assisted pronunciation training. The probabilistic kernel-based method is applied to the audio signal and/or either a principal or an independent component (PCA or ICA) representation of the mouth region in video images. We investigate which representation (PCA or ICA) that may be most suitable and the number of components required in the base, in order to be able to automatically detect pronunciation errors in Swedish from audio-visual input. Experiments performed on one speaker show that the visual information help avoiding classification errors that would lead to gravely erroneous feedback to the user; that it is better to perform phoneme classification on audio and video separately and then fuse the results, rather than combining them before classification; and that PCA outperforms ICA for fewer than 50 components. Index Terms: audiovisual phoneme classification, pronunciation error detection, PCA, ICA

This paper presents an approach to articulatory inversion using audio and video of the user’s face, requiring no special markers. The video is stabilized with respect to the face, and the mouth region cropped out. The mouth image is projected into a learned independent component subspace to obtain a low-dimensional representation of the mouth appearance. The inversion problem is treated as one of regression; a non-linear regressor using relevance vector machines is trained with a dataset of simultaneous images of a subject’s face, acoustic features and positions of magnetic coils glued to the subjects’s tongue. The results show the benefit of using both cues for inversion. We envisage the inversion method to be part of a pronunciation training system with articulatory feedback. Index Terms: audio-visual to articulatory inversion. 1.

This study has been performed in order to evaluate a prototype for the human – computer interface of a computer-based speech training aid named ARTUR. The main feature of the aid is that it can give suggestions on how to improve articulations. Two user groups were involved: three children aged 9 – 14 with extensive experience of speech training with therapists and computers, and three children aged 6, with little or no prior experience of computer-based speech training. All children had general language disorders. The study indicates that the present interface is usable without prior training or instructions, even for the younger children, but that more motivational factors should be introduced. The granularity of the mesh that classifies mispronunciations was satisfactory, but the flexibility and level of detail of the feedback should be developed further.

This study has been performed in order to test the human-machine interface of a computer-based speech training aid named ARTUR with the main feature that it can give suggestions on how to improve articulation. Two user groups were involved: three children aged 9-14 with extensive experience of speech training, and three children aged 6. All children had general language disorders.The study indicates that the present interface is usable without prior training or instructions, even for the younger children, although it needs some improvement to fit illiterate children. The granularity of the mesh that classifies mispronunciations was satisfactory, but can be developed further.

Journal Article A longitudinal study of attitude changes in a medical service organisation after an email introduction Get access O Bälter O Bälter ∗ Department of Numerical Analysis and Computing Science, Royal institute of Technology, Nada, KTH, SE-100 44 Stockholm, Sweden ∗Tel.: +46-8790-6341; fax: +46-810-2477 Search for other works by this author on: Oxford Academic Google Scholar Interacting with Computers, Volume 14, Issue 5, October 2002, Pages 503–519, https://doi.org/10.1016/S0953-5438(02)00012-7 Published: 01 October 2002 Article history Received: 27 November 2001 Revision received: 18 February 2002 Accepted: 24 February 2002 Published: 01 October 2002

Organization of email messages takes an increasing amount of time for many email users. Research has demonstrated that users develop very different strategies to handle this organization. In this paper, the relationship between the different organization strategies and the time necessary to use a certain strategy is illustrated by a mathematical model based on keystroke-level analysis. The model estimates time usage for archiving and retrieving email messages for individual users. Besides explaining why users develop different strategies to organize email messages, the model can also be used to advise users individually when to start using folders, clean messages, learn the search functionality, and using filters to store messages. Similar models could assist evaluation of different interface designs where the number of items increase with time.

All organizations that use email face changes in their email systems. While some of these are only a change of version that has little effect on the organization, many will replace old email systems with new ones, and this may have severe consequences. A case study is presented where the replacement of two old mainframe-based email systems with Lotus Notes failed. Based on this failure, seven important requirements are defined to reduce problems organizations face when replacing old email systems with new ones. These requirements are supported with results from other research.