| 1. |
- Begum, Marjahan, et al.
(författare)
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Empirical Evaluation of a Differentiated Assessment of Data Structures: The Role of Prerequisite Skills
- 2023
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Ingår i: Informatics in Education. An International Journal. - Vilnius : Vilnius University. - 1648-5831 .- 2335-8971. ; 23, s. 57-99
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Tidskriftsartikel (refereegranskat)abstract
- There can be many reasons why students fail to answer correctly to summative tests in advanced computer science courses: often the cause is a lack of prerequisites or misconceptions about topics presented in previous courses. One of the ITiCSE 2020 working groups investigated the possibility of designing assessments suitable for differentiating between fragilities in prerequisites (in particular, knowledge and skills related to introductory programming courses) and advanced topics. This paper reports on an empirical evaluation of an instrument focusing on data structures, among those proposed by the ITiCSE working group. The evaluation aimed at understanding what fragile knowledge and skills the instrument is actually able to detect and to what extent it is able to differentiate them. Our results support that the instrument is able to distinguish between some specific fragilities (e.g., value vs. reference semantics), but not all of those claimed in the original report. In addition, our findings highlight the role of relevant skills at a level between prerequisite and advanced skills, such as program comprehension and reasoning about constraints. We also suggest ways to improve the questions in the instrument, both by improving the distractors of the multiple choice questions, and by slightly changing the content or phrasing of the questions. We argue that these improvements will increase the effectiveness of the instrument in assessing prerequisites as a whole, but also to pinpoint specific fragilities.
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| 2. |
- Ihantola, Petri, et al.
(författare)
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Educational Data Mining and Learning Analytics in Programming : Literature Review and Case Studies
- 2016
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Ingår i: Proceedings of the 2015 ITiCSE on Working Group Reports. - New York, NY, USA : ACM Digital Library. - 9781450341462 ; , s. 41-63
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Konferensbidrag (refereegranskat)abstract
- Educational data mining and learning analytics promise better understanding of student behavior and knowledge, as well as new information on the tacit factors that contribute to student actions. This knowledge can be used to inform decisions related to course and tool design and pedagogy, and to further engage students and guide those at risk of failure. This working group report provides an overview of the body of knowledge regarding the use of educational data mining and learning analytics focused on the teaching and learning of programming. In a literature survey on mining students' programming processes for 2005-2015, we observe a significant increase in work related to the field. However, the majority of the studies focus on simplistic metric analysis and are conducted within a single institution and a single course. This indicates the existence of further avenues of research and a critical need for validation and replication to better understand the various contributing factors and the reasons why certain results occur. We introduce a novel taxonomy to analyse replicating studies and discuss the importance of replicating and reproducing previous work. We describe what is the state of the art in collecting and sharing programming data. To better understand the challenges involved in replicating or reproducing existing studies, we report our experiences from three case studies using programming data. Finally, we present a discussion of future directions for the education and research community.
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| 3. |
- Korhonen, Kimmo, et al.
(författare)
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Particle emissions from a modern heavy-duty diesel engine as ice nuclei in immersion freezing mode: a laboratory study on fossil and renewable fuels
- 2022
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Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7324. ; 22:23, s. 1615-1631
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Tidskriftsartikel (refereegranskat)abstract
- We studied ice-nucleating abilities of particulate emissions from a modern heavy-duty diesel engine using three different types of fuel. The polydisperse particle emissions were sampled during engine operation and introduced to a continuous-flow diffusion chamber (CFDC) instrument at a constant relative humidity RHwater=110 %, while the temperature was ramped between −43 and −32 ∘C (T scan). The tested fuels were EN 590 compliant low-sulfur fossil diesel, hydrotreated vegetable oil (HVO), and rapeseed methyl ester (RME); all were tested without blending. Sampling was carried out at different stages in the engine exhaust aftertreatment system, with and without simulated atmospheric processing using an oxidation flow reactor. In addition to ice nucleation experiments, we used supportive instrumentation to characterize the emitted particles for their physicochemical properties and presented six parameters. We found that the studied emissions contained no significant concentrations of ice-nucleating particles likely to be of atmospheric relevance. The substitution of fossil diesel with renewable fuels, using different emission aftertreatment systems such as a diesel oxidation catalyst, and photochemical aging of total exhaust had only minor effect on their ice-nucleating abilities.
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| 4. |
- Korhonen, Minna, et al.
(författare)
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Elementary field representation of supercontinuum
- 2013
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Ingår i: Journal of the Optical Society of America. B, Optical physics. - 0740-3224 .- 1520-8540. ; 30:1, s. 21-26
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Tidskriftsartikel (refereegranskat)abstract
- We describe the second-order coherence functions of supercontinuum (SC) in terms of elementary fields that can be obtained from measurable average quantities. The representation is based on the partition of the second-order correlation functions of SC into quasi-coherent and quasi-stationary contributions. Numerical simulations of statistical ensembles of SC pulses with different coherence properties are used to illustrate the elementary field model. Comparison with the SC coherent-mode expansion is presented, and we also simulate the propagation of the elementary fields in a dispersive fiber to demonstrate the benefits of the model.
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| 5. |
- Naps, Thomas, et al.
(författare)
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Evaluating the educational impact of visualization
- 2003
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Ingår i: SIGCSE Bulletin inroads. - : Association for Computing Machinery (ACM). - 0097-8418. ; 35:4, s. 124-136
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Tidskriftsartikel (refereegranskat)abstract
- The educational impact of visualization depends not only on how well students learn when they use it, but also on how widely it is used by instructors. Instructors believe that visualization helps students learn. The integration of visualization techniques in classroom instruction, however, has fallen far short of its potential. This paper considers this disconnect, identifying its cause in a failure to understand the needs of a key member in the hierarchy of stakeholders, namely the instructor. We describe these needs and offer guidelines for both the effective deployment of visualizations and the evaluation of instructor satisfaction. We then consider different forms of evaluation and the impact of student learning styles on learner outcomes.
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| 6. |
- Nelson, Greg L., et al.
(författare)
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Differentiated Assessments for Advanced Courses that Reveal Issues with Prerequisite Skills : A Design Investigation
- 2020
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Ingår i: ITICSE-WGR'20. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450382939 ; , s. 75-129
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Konferensbidrag (refereegranskat)abstract
- Computing learners may not master basic concepts, or forget them between courses or from infrequent use. Learners also often struggle with advanced computing courses, perhaps from weakness with prerequisite concepts. One underlying challenge for researchers and instructors is determining the reason why a learner gets an advanced question wrong. Was the wrong answer because the learner lacked prerequisite skills, has not mastered the advanced skill, or some combination of the two? We contribute a design investigation into how to create differentiated questions which diagnose prerequisite and advanced skills at the same time. We focused on tracing and related skills as prerequisites, and on advanced object-oriented programming, concurrency, algorithm and data structures as the advanced skills. We conducted an inductive qualitative analysis of existing assessment questions from instructors and from a concept inventory with a validity argument (the Basic Data Structures Inventory). We found dependencies on a variety of prerequisite knowledge and mixed potential for diagnosing difficulties with prerequisites. Inspired by this analysis, we developed examples of differentiated assessments and reflected on design principles for creating/modifying assessments to better assess both advanced and prerequisite skills. Our example differentiated assessment questions and methods help enable research into how prerequisites skills affect learning of advanced concepts. They also may help instructors better understand and help learners with varying prerequisite knowledge, which may improve equity of learning outcomes. Our work also raises theoretical questions about what assessments really assess and how separate advanced topics and prerequisite skills are.
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| 7. |
- Rößling, Guido, et al.
(författare)
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Enhancing Learning Management Systems to Better Support Computer Science Education
- 2008
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Ingår i: ACM SIGCSE Bulletin: inroads. - : ACM Press. - 0097-8418. ; 40:4, s. 142-166
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Tidskriftsartikel (refereegranskat)abstract
- Many individual instructors -- and, in some cases, entire universities -- are gravitating towards the use of comprehensive learning management systems (LMSs), such as Blackboard and Moodle, for managing courses and enhancing student learning. As useful as LMSs are, they are short on features that meet certain needs specific to computer science education. On the other hand, computer science educators have developed--and continue to develop-computer-based software tools that aid in management, teaching, and/or learning in computer science courses. In this report we provide an overview of current CS specific on-line learning resources and guidance on how one might best go about extending an LMS to include such tools and resources. We refer to an LMS that is extended specifically for computer science education as a Computing Augmented Learning Management System, or CALMS. We also discuss sound pedagogical practices and some practical and technical principles for building a CALMS. However, we do not go into details of creating a plug-in for some specific LMS. Further, the report does not favor one LMS over another as the foundation for a CALMS.
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| 8. |
- Stevens, Robin G., et al.
(författare)
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A model intercomparison of CCN-limited tenuous clouds in the high Arctic
- 2018
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Ingår i: Atmospheric Chemistry And Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 18:15, s. 11041-11071
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Tidskriftsartikel (refereegranskat)abstract
- We perform a model intercomparison of summertime high Arctic ( > 80 degrees N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1 cm(-3). Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNCs) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing. There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts autoconversion rates. Our results therefore suggest that properly estimating aerosol-cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of these clouds is CCN limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures, and atmospheric stability need to be considered for weather and climate predictions in this region.
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