Academic misconduct seems to have increased substantially during the pandemic, with a worldwide upsurge in reported cases. The aim of this project is to construct a framework for helping students engage with issues concerning academic integrity and avoid academic misconduct. This Work-In-Progress paper reports on the construction of a scenario-based framework to investigate the beliefs and attitudes of university stakeholders when confronted with decisions about potential academic misconduct. The framework will be based on using scenarios to spur individual reflections and discussions among the students regarding values related to academic integrity focusing on Uppsala University context. A repository of "misconduct" scenarios related to different cultures, including different views and regulations, is intended to support teachers to develop modules tailored to their current need. The underlying idea is to provide students with an understanding of what constitutes academic misconduct in Uppsala University setting and to help them find honest alternatives when faced with temptations to "cheat". Our view is that students, in general, want to behave honestly, and that this framework will provide a means to help students follow their moral "compass" and avoid dishonest behaviour.

In this full research-to-practice paper we study novice programming students learning process in the computer laboratory. Working with laboratory assignments is an important component when students learn to program. Here the assignments are intended to help students consolidate theoretical understanding and simultaneously train practice. However, it has been observed that the learning outcome of such laboratory sessions often is unsatisfactory. In this article we ask the question "How do novice students go about learning in the computer laboratory?" We analyse empirical data on novice students working in pairs in the laboratory, which is common in a first programming course. The data consists of video films of students where they discuss and solve programming problems, screen captures of what the students typed during the same laboratory session, and stimulated recall interviews with the students after the laboratory session. In the analysis we use an approach inspired by phenomenography and variation theory. We specifically focus on typical stages in the learning process when students learn in the programming laboratory. In doing so we have identified successful and less successful learning paths, where variation can play different roles. The stages identified in students’ learning process are I. Students first need to become aware of a lack of clarity. In the data we have identified different ways in which this necessary awareness was trigged; II. If, and in that case how, they resolve the lack of clarity. In all the stages we found successful and less successful ways in which students’ handle the situations. We illustrate the stages and discuss how and why variation may play different roles in the different stages of students’ learning, specifically focusing of the unsuccessful learning paths. Lastly, we discuss what these findings can tell us about how programming labs could be designed to promote learning in terms of helping students to avoid the unsuccessful paths identified.

SUMMARY: Spatially resolved transcriptomics promises to increase our understanding of the tumor microenvironment and improve cancer prognosis and therapies. Nonetheless, analytical methods to explore associations between the spatial heterogeneity of the tumor and clinical data are not available. Hence, we have developed spatialGE, a software that provides visualizations and quantification of the tumor microenvironment heterogeneity through gene expression surfaces, spatial heterogeneity statistics that can be compared against clinical information, spot-level cell deconvolution and spatially informed clustering, all using a new data object to store data and resulting analyses simultaneously. AVAILABILITY AND IMPLEMENTATION: The R package and tutorial/vignette are available at https://github.com/FridleyLab/spatialGE. A script to reproduce the analyses in this manuscript is available in Supplementary information. The Thrane study data included in spatialGE was made available from the public available from the website https://www.spatialresearch.org/resources-published-datasets/doi-10-1158-0008-5472-can-18-0747/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

It might be a challenge for a STEM researcher to engage in research that is not directly relevant to his or her own field of specialization. The CUP EASTEM course, described in this paper, aims to support academic Asian STEM teachers in overcoming the challenge of researching their own teaching practices. In this paper we discuss, with CUP EASTEM, as a case study, how we have supported academic STEM teachers to take the steps needed to conduct research on their own teaching practices. The key is to broaden the perspective to also include theoretically sound, qualitative interpretative research. Furthermore, this is a journey that must be made without losing sight of the object of the students' learning, that is, the fundamental concepts within the STEM disciplines.

This work-in-progress research discusses the impacts of the student exchange program on Bhutanese Information Technology exchange students. Student exchanges are common among various academic institutions to enhance competency, collaboration, and cultural exchange. For example, an exchange program between the College of Science and Technology, Royal University of Bhutan, Bhutan, a young developing institution, and Uppsala University, Sweden, an old, established university, has witnessed successful bilateral partnerships since 2016. Both partners see the exchange program as fruitful. However, the researchers have not yet researched the outcome of the program on the students. Therefore, in this case study, we study and discuss the influence of the exchange program on the Bhutanese exchange students in this paper. We collected the data from several semi-structured interviews and analyzed the transcripts qualitatively. We asked each student five guiding questions and several follow-up questions. The responses were discussed and jointly investigated by the three first authors. We concluded that studying abroad helps the students to develop in many fields. In this paper, we describe their general experiences, challenges, and growth as perceived by them. Furthermore, the study revealed how the differences between the environments proved to be constructive for the students, as the program contributed to the growth of students, including skills and knowledge.

This research to practice work-in-progress paper discusses some environmental and background factors that motivate the IT students of the College of Science and Technology (CST), Royal University of Bhutan (RUB), to learn programming. Programming is gaining popularity in Bhutan, especially due to the increasing number of opportunities in the IT field. CST is one of the few colleges at RUB providing IT courses to students pursuing undergraduate degrees. Previous studies have revealed that the competence and enthusiasm of first year IT Engineering students at RUB differ between individuals when it comes to learning programming, but the reasons for this are still to be determined. In this paper, we explore factors that influence students of CST to learn programming and what can be done by the college to instil more enthusiasm to learn to program. In this case study, a qualitative research methodology was used to analyse the experiences and opinions of eight IT students of CST. Data was collected through semi-structured interviews and their responses were discussed and jointly analysed by the first three authors. The study revealed several factors such as knowing about future opportunities in IT and partaking in or wanting to partake in activities, social groups and other study related resources which were related to the students' motivation and their encouragement within their studies. Dissimilarities in the attitude towards programming were noted in students despite them having access to the same lecturers, college facilities and other activities. The findings also showed a correlation between the interest in IT and having family or friends engaged in IT related occupations. The study also found that students sometimes felt demotivated by certain factors, such as the initial difficulty of programming, especially among students without prior experience of programming. A similar feeling of discouragement was described when students felt that their peers performed better than them in classes and examinations.

The Covid-19 pandemic has posed major challenges for the education sector worldwide. Face-to-face university courses have to be taught online. University instructors have faced significant difficulties in creating a student-centered learning (SCL) environment online. The aim of this study was to investigate the major challenges of creating student centered learning in Thailand and focused on a population of college instructors attending Thai EASTEM webinar on “Student-Centered Learning in Internet-Based (online) Teaching”, offered in year 2020 during the Covid-19 pandemic. The aims of this webinar series aimed to provide information on student-centered online learning, how to effectively conduct SCL-based online classes and strategies for better assessments in online learning. There were more than 1000 participants attending all three webinars. The online questionnaire was designed to gather information required by the study. Both quantitative and qualitative were analyzed according to emerging aspects of the online learning activity including learning goals, tools & resources, roles and assessment. As results, most instructors had concerned about fairness and honesty in online assessment, how to create SCL online teaching and students' skills in using computer for online learning and students' readiness in terms of equipment. The study findings are of great use in areas of education development in higher institutes of learning. The findings are also of considerable value in creating SCL online learning environment for college teaching in a digital era and adaptation of instructors towards new way of teaching and learning.

This WiP paper discusses difficulties, but also gains, in starting new collaborations, mainly when the universities differ: different natures of their strengths and weaknesses, acting in different contexts and having different international recognitions. At the same time, it is the differences that make exchanges fruitful and opens for new learning experiences. An example of such a collaboration between asymmetric partners can be found in the Department of Information Technology, Uppsala University, Sweden and College of Science and Technology, Royal University of Bhutan.

It often happens that some students come to engage in their learning, and in the learning of their peers, far beyond what we, or they, would have expected. There is also ample evidence of the opposite experience, where students, even if initially highly motivated, end up unable to engage in a meaningful manner. In this paper, we analyse three courses in order to better understand why the level of student engagement varies to such a high degree, with the aim of opening for seeing underlying factors explaining this. Further, we illustrate and discuss our framework with empirical data collected from at Uppsala University. We study the courses using different research approaches (or perspectives), based in the sociocultural tradition, namely Activity Theory (as described by Engeström), Zone of Proximal Development (Vygotsky), and Communities of Practice (Lave & Wenger). These approaches serve as lenses with the aim of finding common factors in the learning environments that are collectively created by the students and their teachers during the extent of the courses. Our results point towards the need to establish a joint understanding between students and teachers at several different levels: at a course level in terms of the aim of a course and its possible outcomes, but also personal aims related to what the course could lead to for everyone involved. Further, our research suggests that the supporting and scaffolding role of the teacher is crucial to the development of a positive learning environment in a course.

We know from research that there is an intimate relationship between student learning and the context of learning. What is not known or understood well enough is the relationship of the students’ background and previous studies to the understanding and learning of the subject area—here, computer science (CS). To show the contextual influences on learning CS, we present empirical data from a qualitative investigation of the experiences of Chinese students studying for a master degree at Sweden's Uppsala University. Data were collected of the students’ understanding and learning of CS, their experience of the teaching and their own studies, and of their personal development in Sweden. Using an analysis framework grounded in phenomenography, we analytically separated the what and how aspects of learning. In this article, we describe the what , or the content of the students’ learning, and identify dimensions of variation in the experiences of students. These dimensions relate to the foci of the CS programs, the learning outcomes, and the impact of the studies. The findings from the analyses indicate pedagogical and pragmatic implications for teaching and learning CS in higher education institutions. The study extends the traditional use of phenomenography through the discussion of the dimensions of variation in the experiences and the values within the dimensions. It opens the way for understanding the relational nature of learning in computing education.

BACKGROUND: Many gene expression normalization algorithms exist for Affymetrix GeneChip microarrays. The most popular of these is RMA, primarily due to the precision and low noise produced during the process. A significant strength of this and similar approaches is the use of the entire set of arrays during both normalization and model-based estimation of signal. However, this leads to differing estimates of expression based on the starting set of arrays, and estimates can change when a single, additional chip is added to the set. Additionally, outlier chips can impact the signals of other arrays, and can themselves be skewed by the majority of the population. RESULTS: We developed an approach, termed IRON, which uses the best-performing techniques from each of several popular processing methods while retaining the ability to incrementally renormalize data without altering previously normalized expression. This combination of approaches results in a method that performs comparably to existing approaches on artificial benchmark datasets (i.e. spike-in) and demonstrates promising improvements in segregating true signals within biologically complex experiments. CONCLUSIONS: By combining approaches from existing normalization techniques, the IRON method offers several advantages. First, IRON normalization occurs pair-wise, thereby avoiding the need for all chips to be normalized together, which can be important for large data analyses. Secondly, the technique does not require similarity in signal distribution across chips for normalization, which can be important for maintaining biologically relevant differences in a heterogeneous background. Lastly, IRON introduces fewer post-processing artifacts, particularly in data whose behavior violates common assumptions. Thus, the IRON method provides a practical solution to common needs of expression analysis. A software implementation of IRON is available at [http://gene.moffitt.org/libaffy/].

Research questions in STEM disciplines are frequently strongly contextualised in the teaching and learning practice of the researcher. In this paper we chart a number of possible paths a researcher can follow from a single research proposition, or fundamental research question, to results which can vary significantly in nature. In order to do this, we establish a theoretical framework for research activity and examine the meaning of “theory” as a cognitive and research tool that helps engineering education practitioners and researchers. The paper reflects on the nature and role of different types of theory at four distinct stages of engineering education research: disciplinary, methodological, analytical, and interpretive. We illustrate how theory applies to the framing and integration of study results, and assists in the process of relating theories of learner development and learning to results of empirical data analysis.

This empirical study demonstrates that students' learning of computer science takes place in qualitatively different ways. The results consists of categories, where each category describe a certain way, in which the students approach their learning. The paper demonstrates that some of the ways to tackle the learning are better than others in resulting in a good learning outcome, and that they therefore should be encouraged. The data, underlying these results, are collected through interviews with third and fourth year students in two countries, and are further analyzed, using a phenomenographic research approach.

What is 'programming thinking'? In a study, first year students were interviewed on their understanding of what learning to program means. Many students talked about learning to program in terms of learning a special way to think, different from other subjects studied. Many of these students had problems in describing what this special way to think included. The analysis of the interviews revealed some features of this thinking, as expressed by the students. In this paper we discuss and analyse 'programming thinking' using phenomenography as our research approach [7]. Our results are coherent with Hazzan's research on the learning theory 'process-object duality' [4], but points to problems in learning of object-oriented programming not indicated in 'process-object duality'. In comparing the results form our own study with this learning theory, we discuss what this might mean in learning object-oriented programming.

BACKGROUND: All eukaryotic organisms need to distinguish each of their chromosomes. A few protein complexes have been described that recognise entire, specific chromosomes, for instance dosage compensation complexes and the recently discovered autosome-specific Painting of Fourth (POF) protein in Drosophila. However, no sequences have been found that are chromosome-specific and distributed over the entire length of the respective chromosome. Here, we present a new, unbiased, exhaustive computational method that was used to probe three Drosophila genomes for chromosome-specific sequences. RESULTS: By combining genome annotations and cytological data with multivariate statistics related to three Drosophila genomes we found sequence signatures that distinguish Muller's F-elements (chromosome 4 in D. melanogaster) from all other chromosomes in Drosophila that are not attributable to differences in nucleotide composition, simple sequence repeats or repeated elements. Based on these signatures we identified complex motifs that are strongly overrepresented in the F-elements and found indications that the D. melanogaster motif may be involved in POF-binding to the F-element. In addition, the X-chromosomes of D. melanogaster and D. yakuba can be distinguished from the other chromosomes, albeit to a lesser extent. Surprisingly, the conservation of the F-element sequence signatures extends not only between species separated by approximately 55 Myr, but also linearly along the sequenced part of the F-elements. CONCLUSION: Our results suggest that chromosome-distinguishing features are not exclusive to the sex chromosomes, but are also present on at least one autosome (the F-element) in Drosophila.

With our interest to improve our education in computer science, an understanding of how students learn about CS concepts, how different concepts are understood, as well as the conditions for learning, become important issues. A better understanding of our students and their learning gives us strong tool in our efforts to develop teaching. There is an increasing awareness of the usefulness of theoretically sound research approaches: it opens for generalisations of results, it invites comparison between researchers, methods and results, and at the same time it makes the limits of the research visible. As examples on initiatives that have lately been taken to promote conscious use of relevant research approaches, can be mentioned the bootstrapping project [13], the special issue on import and export of Computer Science Education (to appear), as well as papers offering overviews of the current use of certain approaches ([4], [8]) and attempts to verbalize models for successful research process ([5], [6], [12]).These initiatives do not advocate the primacy of certain approach over others. This openness is well-grounded, since a particular approach offers certain perspectives on research question, and, in this way, enables the researcher to study [these] aspects of learning, while other aspects, that are not in focus using the selected approach, become unclear or 'blurred' (Berglund, submitted for review). Thus, the selection an approach is closely intertwined with the research question under investigation.In this panel, the theoretical foundations for four different research approaches will be described, and examples of research performed within each of these approaches will be given. The examples will serve to illuminate which kinds of results that can be offered by particular approach, and thereby illustrate its use.

The different ways in which some computer network concepts are understood by students who take an internationally distributed project-based course have been identified in an empirical, qualitative, phenomena graphic research project. The students, who work in teams of six, three in each of the participating countries, collaborate over the Internet to produce a software system which controls a modified version of a toy. Their learning of a computer networking protocols as well as the possibilities to generalize and to deploy the results in teaching situations are presented. The results are useful when seen in the light of the students' learning environment, since relations between the learning outcome and the learning environment can be discerned.

Abstract We have analyzed microarray data using a modeling approach based on the multivariate statistical method partial least squares (PLS) regression to identify genes with periodic fluctuations in expression levels coupled to the cell cycle in the budding yeast, Saccharomyces cerevisiae. PLS has major advantages for analyzing microarray data since it can model data sets with large numbers of variables and with few observations. A response model was derived describing the expression profile over time expected for periodically transcribed genes, and was used to identify budding yeast transcripts with similar profiles. PLS was then used to interpret the importance of the variables (genes) for the model, yielding a ranking list of how well the genes fitted the generated model. Application of an appropriate cutoff value, calculated from randomized data, allows the identification of genes whose expression appears to be synchronized with cell cycling. Our approach also provides information about the stage in the cell cycle where their transcription peaks. Three synchronized yeast cell microarray data sets were analyzed, both separately and combined. Cell cycle-coupled periodicity was suggested for 455 of the 6,178 transcripts monitored in the combined data set, at a significance level of 0.5%. Among the candidates, 85% of the known periodic transcripts were included. Analysis of the three data sets separately yielded similar ranking lists, showing that the method is robust. Contact: [email protected] Supplementary material: Available at: http://www.chem.umu.se/dep/orgchem/forskning/chemometrics/bioinformatic.stm * To whom correspondence should be addressed. † The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

No abstract available.

No abstract available.

We now and then make changes to our courses and how we teach or examine them. This is often done in isolation from other courses that the students take. In this paper we report on experiences made in a coordinated study concerning examination methods. The target group was 60 students from the Systems branch of the Engineering Physics study program. We changed all three courses they took during the first ten weeks of the spring semester 1996. The changes were in short: replace the final exam by weekly assignments, introduce seminars as a method of examination, and in the cases where a written exam was kept, the main focus of the questions were changed to showing understanding, ability to analyze and synthesize.Our experiences in this study clearly show that changing examination is a tool for changing the way our students work, and thus for improving the quality of the education.

article Free Access Share on Evaluation: turning technology from toy to tool: report of the working group on evaluation Authors: Vicki L. Almstrum The University of Texas at Austin The University of Texas at AustinView Profile , Nell Dale The University of Texas at Austin The University of Texas at AustinView Profile , Anders Berglund Uppsala University, Sweden Uppsala University, SwedenView Profile , Mary Granger The George Washington University The George Washington UniversityView Profile , Joyce Currie Little Towson State University Towson State UniversityView Profile , Diane M. Miller University of Southern Mississippi University of Southern MississippiView Profile , Marian Petre Open University, UK Open University, UKView Profile , Paul Schragger Villanova University Villanova UniversityView Profile , Fred Springsteel University of Missouri University of MissouriView Profile Authors Info & Claims ACM SIGCSE BulletinVolume 28Issue SI1996 pp 201–217https://doi.org/10.1145/237477.237648Published:01 January 1996Publication History 22citation906DownloadsMetricsTotal Citations22Total Downloads906Last 12 Months38Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF