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Aligning the goals of learning analytics with its research scholarship. An open peer commentary […]
Ferguson, Rebecca; Khosravi, Hassan; Kovanović, Vitomir; Viberg, Olga; Aggarwal, Ashish; […]
Zeitschriftenbeitrag
| In: Journal of Learning Analytics | 2023
44238 Endnote
Autor*innen:
Ferguson, Rebecca; Khosravi, Hassan; Kovanović, Vitomir; Viberg, Olga; Aggarwal, Ashish; Brinkhuis, Matthieu; Buckingham Shum, Simon; Karen Chen, Lujie; Drachsler, Hendrik; Guerrero, Valerie A.; Hanses, Michael; Hayward, Caitlin; Hicks, Ben; Jivet, Ioana; Kitto, Kirsty; Kizilcec, René; Lodge, Jason M.; Manly, Catherine A.; Matz, Rebecca L.; Meaney, Michael J.; Ochoa, Xavier; Schuetze, Brendan A.; Spruit, Marco; Haastrecht, Max van; Leeuwen, Anouschka van; Rijn, Lars van; Tsai, Yi-Shan; Weidlich, Joshua; Williamson, Kimberly; Yan, Veronica X.
Titel:
Aligning the goals of learning analytics with its research scholarship. An open peer commentary approach
In:
Journal of Learning Analytics, 10 (2023) 2, S. 14-50
DOI:
10.18608/jla.2023.8197
URL:
https://learning-analytics.info/index.php/JLA/article/view/8197
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Sprache:
Englisch
Abstract (english):
To promote cross-community dialogue on matters of significance within the field of learning analytics (LA), we as editors-in-chief of the Journal of Learning Analytics (JLA) have introduced a section for papers that are open to peer commentary. An invitation to submit proposals for commentaries on the paper was released, and 12 of these proposals were accepted. The 26 authors of the accepted commentaries are based in Europe, North America, and Australia. They range in experience from PhD students and early-career researchers to some of the longest-standing, most senior members of the learning analytics community. This paper brings those commentaries together, and we recommend reading it as a companion piece to the original paper by Motz et al. (2023), which also appears in this issue. (DIPF/Orig.)
DIPF-Abteilung:
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Coding energy knowledge in constructed responses with explainable NLP models
Gombert, Sebastian; Di Mitri, Daniele; Karademir, Onur; Kubsch, Marcus; Kolbe, Hannah; […]
Zeitschriftenbeitrag
| In: Journal of Computer Assisted Learning | 2023
43504 Endnote
Autor*innen:
Gombert, Sebastian; Di Mitri, Daniele; Karademir, Onur; Kubsch, Marcus; Kolbe, Hannah; Tautz, Simon; Grimm, Adrian; Bohm, Isabell; Neumann, Knut; Drachsler, Hendrik
Titel:
Coding energy knowledge in constructed responses with explainable NLP models
In:
Journal of Computer Assisted Learning, 39 (2023) 3, S. 767-786
DOI:
10.1111/jcal.12767
URL:
https://onlinelibrary.wiley.com/doi/10.1111/jcal.12767
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Sprache:
Englisch
Abstract (english):
Background : Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free-text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task and requires the application of natural language processing methodology. In this article, we implement and evaluate multiple machine learning models for coding energy knowledge in free-text responses of German K-12 students to items in formative science assessments which were conducted during synchronous online learning sessions. Dataset : The dataset we collected for this purpose consists of German constructed responses from 38 different items dealing with aspects of energy such as manifestation and transformation. The units and items were implemented with the help of project-based pedagogy and evidence-centered design, and the responses were coded for seven core ideas concerning the manifestation and transformation of energy. The data was collected from students in seventh, eighth and ninth grade. Methodology : We train various transformer- and feature-based models and compare their ability to recognize the respective ideas in students' writing. Moreover, as domain knowledge and its development can be formally modeled through knowledge networks, we evaluate how well the detection of the ideas within responses translated into accurate co-occurrence-based knowledge networks. Finally, in terms of the descriptive accuracy of our models, we inspect what features played a role for which prediction outcome and if the models pick up on undesired shortcuts. In addition to this, we analyze how much the models match human coders in what evidence within responses they consider important for their coding decisions. Results : A model based on a modified GBERT-large can achieve the overall most promising results, although descriptive accuracy varies much more than predictive accuracy for the different ideas assessed. For reasons of comparability, we also evaluate the same machine learning architecture using the SciEntsBank 3-Way benchmark with an English RoBERTa-large model, where it achieves state-of-the-art results in two out of three evaluation categories. (DIPF/Orig.)
DIPF-Abteilung:
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Measuring efficacy of ALEKS as a supportive instructional tool in K-12 math classroom with […]
Khazanchi, Rashmi; Di Mitri, Daniele; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: Journal of Computers in Mathematics and Science Teaching | 2023
44453 Endnote
Autor*innen:
Khazanchi, Rashmi; Di Mitri, Daniele; Drachsler, Hendrik
Titel:
Measuring efficacy of ALEKS as a supportive instructional tool in K-12 math classroom with underachieving students
In:
Journal of Computers in Mathematics and Science Teaching, 42 (2023) 2, S. 155-176
URL:
https://www.learntechlib.org/noaccess/221775/
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
This quasi-experimental research study examines whether the use of Assessment and Learning in Knowledge Spaces (ALEKS), an ITS, shows a statistically significant improvement in students' mathematics achievement than traditional teacher-led instructions. This non-randomized research study measured the efficacy of ALEKS on 'underachieving students' mathematics achievement among 158 (60 in teacher-led group and 98 in ALEKS-led group) 8th-grade students. A pretest and posttest were employed between teacher-led instructions versus ALEKS-led instructions from two consecutive years. During the first year, only McGraw's curriculum "Reveal" was used with no use of ALEKS. In the second year, the school implemented ALEKS as a supplemental tool in a math support class for fifty minutes every other day for a year to provide instruction to struggling students along with McGraw's curriculum "Reveal." We also compare the results of five years of End of Grade (EOG) without ALEKS with one-year EOG with the use of ALEKS. Data were analyzed using paired t-test and analysis of covariance (ANOVA) to evaluate the efficacy of ALEKS on students' mathematics achievement. We find that the results of ALEKS-led and teacher-led instructions are highly statistically significant. The results show that teacher-led instructions are more effective because of higher test scores and lower variance for teacher-led instructions.
DIPF-Abteilung:
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Hacking gender in computer-supported collaborative learning. The experience of being in […]
Kube, Dana; Gombert, Sebastian; Suter, Brigitte; Weidlich, Joshua; Kreijns, Karel; […]
Zeitschriftenbeitrag
| In: Journal of Computer Assisted Learning | 2023
44451 Endnote
Autor*innen:
Kube, Dana; Gombert, Sebastian; Suter, Brigitte; Weidlich, Joshua; Kreijns, Karel; Drachsler, Hendrik
Titel:
Hacking gender in computer-supported collaborative learning. The experience of being in mixed-gender teams at a computer science hackathon
In:
Journal of Computer Assisted Learning, (2023) , S. online first
DOI:
https://doi.org/10.1111/jcal.12905
URL:
https://onlinelibrary.wiley.com/doi/10.1111/jcal.12905
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
Background Gender stereotypes about women and men are prevalent in computer science (CS). The study's goal was to investigate the role of gender bias in computer-supported collaborative learning (CSCL) in a CS context by elaborating on gendered experiences in the perception of individual and team performance in mixed-gender teams in a hackathon. Dataset The dataset of this study was collected at a 3-day CSCL hackathon aimed at gaining knowledge on designing educational games. We assigned the 28 participants of the hackathon to mixed-gender groups and asked them to fill out a questionnaire, including collective self-esteem scales, before the start. During the hackathon, we again asked the participants to complete team progress evaluation surveys individually after each workday. Lastly, we interviewed 11 participants to elaborate on the quantitative findings with qualitative data. Methodology We applied an exploratory mixed-method approach using quantitative survey data at several time points during the hackathon, which was analysed with clustering and descriptive statistics and complemented with qualitative coding of interviews with participants. Results The results demonstrate that social and psychological aspects of gender are important for understanding the outcomes and perceptions of gender in a CS hackathon. The analysis further suggests that collective self-esteem can be used as a key variable to assess gender differences in CSCL studies, providing explanatory benefits. More broadly, results gave reason to believe that CSCL in the CS domain currently severely fails to account for gender representation. Interviewed participants raised substantial concerns about the underlying gender stereotypes prevalent in communication, team roles, and work division. We provide recommendations for practitioners seeking to create gender-inclusive and counter-stereotypical CSCL and wider, critical proposals for how we, as researchers, can assess gender with appropriate methodologies and interventions in computer science education. Lay Description What is already known about this topic? In the field of computer-supported collaborative learning (CSCL), most studies argue that group work supports the development of social, cognitive, and online collaborative teamwork skills and creates a more inclusive learning environment. Because women represent non-majority users in CSCL, especially when applied in the computer science domain, this notion is questioned by studies finding that diversity inclusion in CSCL is hampered through gender stereotypes still present in CS and impacts women's and other gender minorities' learning experiences. Another problem is that the role of gender in CSCL research has scarcely been addressed by the CSCL community yet. Thus, research methodologies trying to reveal gender differences seldomly address gender majority-minority relations in learning in understanding the role of gender in shaping these learning experiences. What this paper adds? Emerging from this research gap, the main contribution of our study is to investigate the validity and explanatory power of operationalizations of gender that consider gender not as the biological sex of the learner but as a social construct operating in the specific learning context. Thus, we demonstrate the benefits of considering differentiation in gender identity and gender perception to understand differences in individual learning experiences and the role of gender in the context of a CSCL hackathon in computer science education. We draw on an innovative exploratory mixed method design to contribute to the methodological discourse in CSCL research concerning gender. Specifically, we demonstrate how gender differences in perceptions of mixed-gender groups can be meaningfully operationalised via the social and psychological aspects of gender in CSCL in CS that is gender identity, self-esteem and belonging in computer science CSCL. The implications of study findings for practitioners This study gives the following recommendations for CSCL technical and pedagogical designers: (1) Designing with and for women and minority-specific privacy considerations. (2) Creating gender-representative and gender-affirming communication infrastructures, counter-stereotypical roles in the teams and gender-balanced group constellation, along with pedagogical and teaching practice that is open for including women's perspectives in grounded and participatory design processes. (3) In terms of CSCL hackathons, I might also consider doing community-based hackathons that attract women and minorities, for instance, through connecting women and minority non-profit organisations with student developers, as in "Think Global Hack Local Hackathons".
DIPF-Abteilung:
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Evaluating the impact of FoLA2 on learning analytics knowledge creation and acceptance during the […]
Schmitz, Marcel; Scheffel, Maren; Bemelmans, Roger; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: Interaction Design and Architecture(s) Journal | 2023
43754 Endnote
Autor*innen:
Schmitz, Marcel; Scheffel, Maren; Bemelmans, Roger; Drachsler, Hendrik
Titel:
Evaluating the impact of FoLA2 on learning analytics knowledge creation and acceptance during the co-design of learning activities
In:
Interaction Design and Architecture(s) Journal, (2023) 55, S. 9-33
DOI:
10.55612/s-5002-055-001
URL:
https://ixdea.org/55_1/
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Sprache:
Englisch
Abstract:
Learning analytics offers opportunities to enhance the design of learning activities by providing information on the impact of different learning designs. Despite the availability of design methods that aim to facilitate the integration of learning analytics in learning design, there is a lack of research evaluating their effectiveness. This study aims to assess the effectiveness of the FoLA2 method. Sixty participants utilized the FoLA2 method to create fourteen learning activities in higher education settings. To measure the impact, participants completed a technology acceptance test both before and after each session. Additionally, the researchers analyzed audio recordings of the sessions using epistemic network analysis to gain insights into the discussions surrounding learning analytics and the design of enriched learning activities. The results of both the technology acceptance test and the epistemic network analysis indicated that the FoLA2 method effectively supports the integration of learning analytics during the design of learning activities. (DIPF/Orig.)
DIPF-Abteilung:
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Causal reasoning with causal graphs in educational technology research
Weidlich, Joshua; Hicks, Ben; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: Educational Technology Research and Development | 2023
43745 Endnote
Autor*innen:
Weidlich, Joshua; Hicks, Ben; Drachsler, Hendrik
Titel:
Causal reasoning with causal graphs in educational technology research
In:
Educational Technology Research and Development, 2023 (2023) , S. online first
DOI:
10.1007/s11423-023-10241-0
URL:
https://link.springer.com/article/10.1007/s11423-023-10241-0
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given the complexities of studying learning in authentic contexts interwoven with technological affordances, conducting tightly-controlled randomized experiments is not always feasible nor desirable. Today, a set of tools is available that can help researchers reason about cause-and-effect, irrespective of the particular research design or approach. This theoretical paper introduces such a tool, a simple graphical formalism that can be used to reason about potential sources of bias. We further explain how causal graphs differ from structural equation models and highlight the value of explicit causal inference. The final section shows how causal graphs can be used in several stages of the research process, whether researchers plan to conduct observational or experimental research. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Students' feedback literacy in higher education: an initial scale validation study
Woitt, Svenja; Weidlich, Joshua; Jivet, Ioana; Orhan Göksün, Derya; Drachsler, Hendrik; Kalz, Marco
Zeitschriftenbeitrag
| In: Teaching in Higher Education | 2023
44296 Endnote
Autor*innen:
Woitt, Svenja; Weidlich, Joshua; Jivet, Ioana; Orhan Göksün, Derya; Drachsler, Hendrik; Kalz, Marco
Titel:
Students' feedback literacy in higher education: an initial scale validation study
In:
Teaching in Higher Education, (2023) , S. online first
DOI:
https://doi.org/10.1080/13562517.2023.2263838
URL:
https://www.tandfonline.com/doi/full/10.1080/13562517.2023.2263838
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
Given the crucial role of feedback in supporting learning in higher education, understanding the factors influencing feedback effectiveness is imperative. Student feedback literacy, that is, the set of attitudes and abilities to make sense of and utilize feedback is therefore considered a key concept. Rigorous investigations of feedback literacy require psychometrically sound measurement. To this end, the present paper reports on the development and initial validation (N = 221) of a self-report instrument. Grounded in the conceptual literature and building on previous scale validation efforts, an initial overinclusive item pool is generated. Exploratory factor analysis and the Rasch measurement model yield adequate psychometric properties of an initial scale measuring two dimensions: feedback attitudes and feedback practices with a total of 21 items. We further provide evidence for criterion-related validity. Findings are discussed in light of the emerging feedback literacy literature and avenues for further improvement of the scale are reported.
DIPF-Abteilung:
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Students' expectations of Learning Analytics across Europe
Wollny, Sebastian; Di Mitri, Daniele; Jivet, Ioana; Muñoz-Merino, Pedro; Scheffel, Maren; […]
Zeitschriftenbeitrag
| In: Journal of Computer Assisted Learning | 2023
43542 Endnote
Autor*innen:
Wollny, Sebastian; Di Mitri, Daniele; Jivet, Ioana; Muñoz-Merino, Pedro; Scheffel, Maren; Schneider, Jan; Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gašević, Dragan; Drachsler, Hendrik
Titel:
Students' expectations of Learning Analytics across Europe
In:
Journal of Computer Assisted Learning, 39 (2023) 4, S. 1325-1338
DOI:
10.1111/jcal.12802
URL:
https://onlinelibrary.wiley.com/doi/10.1111/jcal.12802
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
Background : Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners and their contexts to gain insights into learning processes. As the technology of Learning Analytics is evolving, many systems are being implemented. In this context, it is essential to understand stakeholders' expectations of LA across Higher Education Institutions (HEIs) for large-scale implementations that take their needs into account. Objectives : This study aims to contribute to knowledge about individual LA expectations of European higher education students. It may facilitate the strategy of stakeholder buy-in, the transfer of LA insights across HEIs, and the development of international best practices and guidelines. Methods : To this end, the study employs a 'Student Expectations of Learning Analytics Questionnaire' (SELAQ) survey of 417 students at the Goethe University Frankfurt (Germany) Based on this data, Multiple Linear Regressions are applied to determine how these students position themselves compared to students from Madrid (Spain), Edinburgh (United Kingdom) and the Netherlands, where SELAQ had already been implemented at HEIs. Results and Conclusions : The results show that students' expectations at Goethe University Frankfurt are rather homogeneous regarding 'LA Ethics and Privacy' and 'LA Service Features'. Furthermore, we found that European students generally show a consistent pattern of expectations of LA with a high degree of similarity across the HEIs examined. European HEIs face challenges more similar than anticipated. The HEI experience with implementing LA can be more easily transferred to other HEIs, suggesting standardized LA rather than tailor-made solutions designed from scratch. (DIPF/Orig.)
DIPF-Abteilung:
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LAxplore: An NLP-based tool for distilling learning analytics and learning design instruments out […]
Ahmad, Atezaz; Schneider, Jan; Schiffner, Daniel; Islamovic, Esad; Drachsler, Hendrik
Sammelbandbeitrag
| Aus: Fred, Ana; Coenen, Frans; Bernardino, Jorge (Hrsg.): Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, November 13-15, in Rome, Italy | Setúbal: SciTePress | 2023
44460 Endnote
Autor*innen:
Ahmad, Atezaz; Schneider, Jan; Schiffner, Daniel; Islamovic, Esad; Drachsler, Hendrik
Titel:
LAxplore: An NLP-based tool for distilling learning analytics and learning design instruments out of scientific publications
Aus:
Fred, Ana; Coenen, Frans; Bernardino, Jorge (Hrsg.): Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, November 13-15, in Rome, Italy, Setúbal: SciTePress, 2023 , S. 230-239
DOI:
10.5220/0012163600003598
URL:
https://www.scitepress.org/Link.aspx?doi=10.5220/0012163600003598
Dokumenttyp:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Sprache:
Englisch
Abstract (english):
Each year, the amount of research publications is increasing. Staying on top of the state of the art is a pressing issue. The field of Learning Analytics (LA) is no exception, with the rise of digital education systems that are used broadly these days from K12 up to Higher Education. Keeping track of the advances in LA is challenging. This is especially the case for newcomers to the field, as well as for the increasing number of LA units that consult their teachers and scholars on applying evidence-based research outcomes in their lectures. To keep an overview of the rapidly growing research findings on LA, we developed LAxplore, a tool that uses NLP to extract relevant information from the LA literature. In this article, we present the evaluation of LAxplore. Results from the evaluation show that LAxplore can significantly support researchers in extracting information from relevant LA publications as it reduces the time of searching and retrieving the knowledge by a factor of six. However, the accurate extraction of relevant information from LA literature is not yet ready to be fully automatized and some manual work is still required.
DIPF-Abteilung:
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A trusted learning analytics dashboard for displaying OER
Ahmad, Atezaz; Yordanov, Ivaylo Ivanov; Yau, Jane; Schneider, Jan; Drachsler, Hendrik
Sammelbandbeitrag
| Aus: Otto, Daniel; Scharnberg, Gianna; Kerres, Michael; Zawacki-Richter, Olaf (Hrsg.): Distributed learning ecosystems: Concepts, resources, and repositories | Wiesbaden: Springer | 2023
43376 Endnote
Autor*innen:
Ahmad, Atezaz; Yordanov, Ivaylo Ivanov; Yau, Jane; Schneider, Jan; Drachsler, Hendrik
Titel:
A trusted learning analytics dashboard for displaying OER
Aus:
Otto, Daniel; Scharnberg, Gianna; Kerres, Michael; Zawacki-Richter, Olaf (Hrsg.): Distributed learning ecosystems: Concepts, resources, and repositories, Wiesbaden: Springer, 2023 , S. 279-303
DOI:
10.1007/978-3-658-38703-7_15
URL:
https://link.springer.com/chapter/10.1007/978-3-658-38703-7_15
Dokumenttyp:
4. Beiträge in Sammelbänden; Sammelband (keine besondere Kategorie)
Sprache:
Englisch
Schlagwörter:
Datenanalyse; Datenerfassung; Indikator; Internetplattform; Learning Analytics; Lernplattform; Literaturbericht; Open Educational Resources; Technologie
Abstract:
Learning Analytics (LA) consists of miscellaneous steps that include data harvesting, storing, cleaning, anonymisation, mining, analysis, and visualisation so that the vast amount of educational data is comprehensible and ethically utilisable by educators or instructors to obtain the advantages and benefits that LA can bring to the educational scene. These include the potential to increase learning experiences and reduce dropout rates. In this chapter, we shed light on OER repositories, LA, and LA dashboards and present an implementation of a research-driven LA dashboard for displaying OER and their repositories that allows the visualisation of educational data in an understandable way for both educators and learners. Moreover, we present an LA dashboard for displaying OER that shows information about the existing German OER repositories as part of our EduArc project located in Germany. The LA dashboard consists of multiple adopted indicators and metrics such as the number of reading sessions, duration of reading sessions, number of reading interruptions, number of learning activities, student attendance, and student grades. The details of the research methodology, including a literature review to create this dashboard, as well as the display items of the dashboard are presented and further elaborated. (DIPF/Autor)
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