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Connecting the dots - a literature review on learning analytics indicators from a learning design […]
Ahmad, Atezaz; Schneider, Jan; Griffiths, Dai; Biedermann, Daniel; Schiffner, Daniel; […]
Zeitschriftenbeitrag
| In: Journal of Computer Assisted Learning | 2022
42917 Endnote
Autor*innen:
Ahmad, Atezaz; Schneider, Jan; Griffiths, Dai; Biedermann, Daniel; Schiffner, Daniel; Greller, Wolfgang; Drachsler, Hendrik
Titel:
Connecting the dots - a literature review on learning analytics indicators from a learning design perspective
In:
Journal of Computer Assisted Learning, (2022) , S. online first
DOI:
10.1111/jcal.12716
URL:
https://onlinelibrary.wiley.com/doi/full/10.1111/jcal.12716
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Sprache:
Englisch
Abstract (english):
During the past decade, the increasingly heterogeneous field of learning analytics has been critiqued for an over-emphasis on data-driven approaches at the expense of paying attention to learning designs. In response to this critique, we investigated the role of learning design in learning analytics through a systematic literature review. 161 learning analytics (LA) articles were examined to identify indicators that were based on learning design events and their associated metrics. Through this research, we address two objectives. First, to achieve a better alignment between learning design and learning analytics by proposing a reference framework, where we present possible connections between learning analytics and learning design. Second, to present how LA indicators and metrics have been researched and applied in the past. In our review, we found that a number of learning analytics papers did indeed consider learning design activities for harvesting user data. We also found a consistent increase in the number and quality of indicators and their evolution over the years. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Keep me in the loop. Real-time feedback with multimodal data
Di Mitri, Daniele; Schneider, Jan; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: International Journal of Artificial Intelligence in Education | 2022
43531 Endnote
Autor*innen:
Di Mitri, Daniele; Schneider, Jan; Drachsler, Hendrik
Titel:
Keep me in the loop. Real-time feedback with multimodal data
In:
International Journal of Artificial Intelligence in Education, 32 (2022) 4, S. 1093-1118
DOI:
10.1007/s40593-021-00281-z
URL:
https://link.springer.com/article/10.1007/s40593-021-00281-z
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Schlagwörter:
Datenanalyse; Datenverarbeitung; Effektivität; Empirische Untersuchung; Feedback; Fehler; Fertigkeit; Fragebogen; Lernprozess; Medizin; Psychomotorik; Simulation; System; Technologie; Teilnehmer; Tool; Training
Abstract (english):
This paper describes the CPR Tutor, a real-time multimodal feedback system for cardiopulmonary resuscitation (CPR) training. The CPR Tutor detects training mistakes using recurrent neural networks. The CPR Tutor automatically recognises and assesses the quality of the chest compressions according to five CPR performance indicators. It detects training mistakes in real-time by analysing a multimodal data stream consisting of kinematic and electromyographic data. Based on this assessment, the CPR Tutor provides audio feedback to correct the most critical mistakes and improve the CPR performance. The mistake detection models of the CPR Tutor were trained using a dataset from 10 experts. Hence, we tested the validity of the CPR Tutor and the impact of its feedback functionality in a user study involving additional 10 participants. The CPR Tutor pushes forward the current state of the art of real-time multimodal tutors by providing: (1) an architecture design, (2) a methodological approach for delivering real-time feedback using multimodal data and (3) a field study on real-time feedback for CPR training. This paper details the results of a field study by quantitatively measuring the impact of the CPR Tutor feedback on the performance indicators and qualitatively analysing the participants' questionnaire answers. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Learning analytics in higher education. Stakeholders, strategy and scale
Gašević, Dragan; Tsai, Yi-Shan; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: The Internet and Higher Education | 2022
42489 Endnote
Autor*innen:
Gašević, Dragan; Tsai, Yi-Shan; Drachsler, Hendrik
Titel:
Learning analytics in higher education. Stakeholders, strategy and scale
In:
The Internet and Higher Education, 52 (2022) , S. 100833
DOI:
10.1016/j.iheduc.2021.100833
URL:
https://www.sciencedirect.com/science/article/abs/pii/S1096751621000427?via%3Dihub
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Bibliografien/Rezensionen u.ä. (z.B. Linktipps)
Sprache:
Englisch
DIPF-Abteilung:
Informationszentrum Bildung
"Gendered differences versus doing gender" A systematic review on the role of gender in CSCL
Kube, Jana; Weidlich, Joshua; Jivet, Ioana; Kreijns, Karel; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: Unterrichtswissenschaft | 2022
42972 Endnote
Autor*innen:
Kube, Jana; Weidlich, Joshua; Jivet, Ioana; Kreijns, Karel; Drachsler, Hendrik
Titel:
"Gendered differences versus doing gender" A systematic review on the role of gender in CSCL
In:
Unterrichtswissenschaft, 50 (2022) 4, S. 661-688
DOI:
10.1007/s42010-022-00153-y
URL:
https://link.springer.com/article/10.1007/s42010-022-00153-y
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
Gender equity in education is an essential UN sustainable development goal. However, it is unclear what aspects of gender are important to consider in regard to research outcomes as well as how findings can be interpreted in the context of gender stereotypes and bias. This lack of clarity is particularly salient in the STEM field. Computer-supported collaborative learning (CSCL) is a group learning method where learners work together on group tasks that aim at the sharing and co-construction of knowledge. Aside from the cognitive learning gains, the literature reports that CSCL can bring social and psychological benefits, such as fostering positive mutual relationships and increased understanding of equity and diversity. In order to elaborate on the assumed potential of CSCL to support equity and diversity goals in education, this systematic literature will focus on the role of gender in CSCL. Although gender issues in CSCL have been examined before, a comprehensive overview is still lacking. Based on the PRISMA method, the current systematic review considers 27 articles, and explores (1) how gender is addressed, (2) what findings concerning gender are reported, and (3) the potential of CSCL to create more gender inclusive learning contributing to the UN SDGs. Our findings show that most studies addressed gender as a binary predictor for participation, communication, or attitude. Less than half of the studies treated gender more nuanced by defining gender as a social construct. This review highlights the need for additional research on the role of gender in CSCL, alongside more methodologies that can account for the complexities this entails. It is estimated that there is some potential for CSCL to decrease gender stereotypes and gender bias in STEM education. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Toward learning progression analytics. Developing learning environments for the automated analysis […]
Kubsch, Marcus; Czinczel, Berrit; Lossjew, Jannik; Wyrwich, Tobias; Bednorz, David; […]
Zeitschriftenbeitrag
| In: Frontiers in Education | 2022
42973 Endnote
Autor*innen:
Kubsch, Marcus; Czinczel, Berrit; Lossjew, Jannik; Wyrwich, Tobias; Bednorz, David; Bernholt, Sascha; Fiedler, Daniela; Strauß, Sebastian; Cress, Ulrike; Drachsler, Hendrik; Neumann, Knut; Rummel, Nikol
Titel:
Toward learning progression analytics. Developing learning environments for the automated analysis of learning using evidence centered design
In:
Frontiers in Education, 7 (2022) , S. 981910
DOI:
10.3389/feduc.2022.981910
URL:
https://www.frontiersin.org/articles/10.3389/feduc.2022.981910/full
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
National educational standards stress the importance of science and mathematics learning for today's students. However, across disciplines, students frequently struggle to meet learning goals about core concepts like energy. Digital learning environments enhanced with artificial intelligence hold the promise to address this issue by providing individualized instruction and support for students at scale. Scaffolding and feedback, for example, are both most effective when tailored to students' needs. Providing individualized instruction requires continuous assessment of students' individual knowledge, abilities, and skills in a way that is meaningful for providing tailored support and planning further instruction. While continuously assessing individual students' science and mathematics learning is challenging, intelligent tutoring systems show that it is feasible in principle. However, the learning environments in intelligent tutoring systems are typically not compatible with the vision of how effective K-12 science and mathematics learning looks like. This leads to the challenge of designing digital learning environments that allow for both - meaningful science and mathematics learning and the reliable and valid assessment of individual students' learning. Today, digital devices such as tablets, laptops, or digital measurement systems increasingly enter science and mathematics classrooms. In consequence, students' learning increasingly produces rich product and process data. Learning Analytics techniques can help to automatically analyze this data in order to obtain insights about individual students' learning, drawing on general theories of learning and relative to established domain specific models of learning, i.e., learning progressions. We call this approach Learning Progression Analytics (LPA). In this manuscript, building of evidence-centered design (ECD), we develop a framework to guide the development of learning environments that provide meaningful learning activities and data for the automated analysis of individual students' learning - the basis for LPA and scaling individualized instruction with artificial intelligence. (DIPF/Orig.)
DIPF-Abteilung:
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FoLA2 - a method for co-creating learning analytics-supported learning design
Schmitz, Marcel; Scheffel, Maren; Bemelmans, Roger; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: Journal of Learning Analytics | 2022
43214 Endnote
Autor*innen:
Schmitz, Marcel; Scheffel, Maren; Bemelmans, Roger; Drachsler, Hendrik
Titel:
FoLA2 - a method for co-creating learning analytics-supported learning design
In:
Journal of Learning Analytics, 9 (2022) 2, S. 265-281
DOI:
10.18608/jla.2022.7643
URL:
https://learning-analytics.info/index.php/JLA/article/view/7861
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Sprache:
Englisch
Abstract:
Learning activities are at the core of every educational design effort. Designing learning activities is a process that benefits from reflecting on previous runs of those activities. One way to measure the behaviour and effects of design choices is to use learning analytics (LA). The challenge, however, lies in the unavailability of an easy-to-use, LA-supported learning design (LD) method. We established such a method-the Fellowship of Learning Activities and Analytics (FoLA2)-reinforced by a gameboard and cards, to provide structure and inspiration. The method enables several participants with different roles to interact with a set of card decks to collaboratively create an LA-supported LD. Using this method helps to design learning activities in a collaborative, practical way; it also raises awareness about the benefits of multidisciplinary co-design and connections between LA and LD. FoLA2 can be used to develop, capture, and systematize design elements and to systematically incorporate LA.
DIPF-Abteilung:
Informationszentrum Bildung
Are the World Health Organization's patient safety learning objectives still up-to-date. A group […]
Vogt, Lina; Stoyanov, Slavi; Bergs, Jochen; Schröder, Hanna; Drachsler, Hendrik; Klasen, Martin; […]
Zeitschriftenbeitrag
| In: Journal of Patient Safety | 2022
42527 Endnote
Autor*innen:
Vogt, Lina; Stoyanov, Slavi; Bergs, Jochen; Schröder, Hanna; Drachsler, Hendrik; Klasen, Martin; Sopka, Saša
Titel:
Are the World Health Organization's patient safety learning objectives still up-to-date. A group concept mapping study
In:
Journal of Patient Safety, 18 (2022) 8, S. 731-737
DOI:
10.1097/PTS.0000000000000993
URL:
https://journals.lww.com/journalpatientsafety/abstract/9000/are_the_world_health_organization_s_patient_safety.98882.aspx
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Aufsatz (keine besondere Kategorie)
Sprache:
Englisch
Abstract:
Background: The World Health Organization (WHO) Patient Safety Curriculum Guide defines learning objectives for patient safety. Current implementation in healthcare education is insufficient. Possible explanations may be obsolescence and/or a shift in needs. We investigated whether overarching topics and specific learning objectives of the WHO Patient Safety Curriculum Guide are still up-to-date, their attributed importance, and their perceived difficulty to achieve. Methods: Experts on patient safety and medical education from 3 European countries were asked to suggest learning objectives concerning patient safety using group concept mapping. Following 3 successive steps, experts rated ideas by importance and difficulty to achieve. Correlation analyses investigated the relationship between those. Overarching topics of the learning goals (clusters) were identified with multivariate analysis. Results: A total of 119 statements about intended learning objectives on patient safety were generated, of which 86 remained for sorting and rating. Based on multivariate analyses, 10 overarching topics (clusters) emerged. Both the learning objectives and the overarching topics showed high correspondence with the WHO Patient Safety Curriculum Guide. Strong correlations emerged between importance and difficulty ratings for learning objectives and overarching topics. Conclusions: The WHO Patient Safety Curriculum Guide's learning goals are still relevant and up-to-date. Remarkably, learning objectives categorized as highly important are also perceived as difficult to achieve. In summary, the insufficient implementation in medical curricula cannot be attributed to the content of the learning goals. The future focus should be on how the WHO learning goals can be implemented in existing curricular courses. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
Causal inference and bias in learning analytics. A primer on pitfalls using directed acyclic graphs
Weidlich, Joshua; Gašević, Dragan; Drachsler, Hendrik
Zeitschriftenbeitrag
| In: Journal of Learning Analytics | 2022
43087 Endnote
Autor*innen:
Weidlich, Joshua; Gašević, Dragan; Drachsler, Hendrik
Titel:
Causal inference and bias in learning analytics. A primer on pitfalls using directed acyclic graphs
In:
Journal of Learning Analytics, 9 (2022) 3, S. 183-199
DOI:
10.18608/jla.2022.7577
URL:
https://learning-analytics.info/index.php/JLA/article/view/7577
Dokumenttyp:
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft
Sprache:
Englisch
Abstract:
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they may be reluctant to draw causal inferences. The past decades have seen much progress concerning causal inference in the absence of experimental data. This paper introduces directed acyclic graphs (DAGs), an increasingly popular tool to visually determine the validity of causal claims. Based on this, three basic pitfalls are outlined: confounding bias, overcontrol bias, and collider bias. Further, the paper shows how these pitfalls may be present in the published LA literature alongside possible remedies. Finally, this approach is discussed in light of practical constraints and the need for theoretical development. (DIPF/Orig.)
DIPF-Abteilung:
Informationszentrum Bildung
What indicators can I serve you with? An evaluation of a research-driven learning analytics […]
Ahmad, Atezaz; Schneider, Jan; Weidlich, Joshua; Di Mitri, Daniele; Yau, Jane; Schiffner, Daniel; […]
Sammelbandbeitrag
| Aus: Cukurova, Mutlu; Rummel, Nikol; Gillet, Denis; McLaren, Bruce; Uhumoibhi, James (Hrsg.): Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022) | Setúbal: Science and Technology Publications | 2022
42668 Endnote
Autor*innen:
Ahmad, Atezaz; Schneider, Jan; Weidlich, Joshua; Di Mitri, Daniele; Yau, Jane; Schiffner, Daniel; Drachsler, Hendrik
Titel:
What indicators can I serve you with? An evaluation of a research-driven learning analytics indicator repository
Aus:
Cukurova, Mutlu; Rummel, Nikol; Gillet, Denis; McLaren, Bruce; Uhumoibhi, James (Hrsg.): Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022), Setúbal: Science and Technology Publications, 2022 , S. 58-68
DOI:
10.5220/0010995800003182
URL:
https://www.scitepress.org/PublicationsDetail.aspx?ID=5+qOb5wAQsA=&t=1
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Abstract (english):
In recent years, Learning Analytics (LA) has become a very heterogeneous research field due to the diversity in the data generated by the Learning Management Systems (LMS) as well as the researchers in a variety of disciplines, who analyze this data from a range of perspectives. In this paper, we present the evaluation of a LA tool that helps course designers, teachers, students and educational researchers to make informed decisions about the selection of learning activities and LA indicators for their course design or LA dashboard. The aim of this paper is to present Open Learning Analytics Indicator Repository (OpenLAIR) and provide a first evaluation with key stakeholders (N=41). Moreover, it presents the results of the prevalence of indicators that have been used over the past ten years in LA. Our results show that OpenLAIR can support course designers in designing LA-based learning activities and courses. Furthermore, we found a significant difference between the relevance and usage of LA indicators between educators and learners. The top rated LA indicators by researchers and educators were not perceived as equally important from students' perspectives.
DIPF-Abteilung:
Informationszentrum Bildung
How can interaction data be contextualized with mobile sensing to enhance learning engagement […]
Ciordas-Hertel, George-Petru; Biedermann, Daniel; Winter, Marc; Mordel, Julia; Drachsler, Hendrik
Sammelbandbeitrag
| Aus: Tumuluri, Raj; Sebe, Nicu; Pingali, Gopal; Jayagopi, Dinesh Babu; Dhall, Abhinav; Singh, Richa; Anthony, Lisa; Ali Salah, Albert (Hrsg.): ICMI '22 companion: Companion publication of the 2022 International Conference on Multimodal Interaction | New York; NY: Association for Computing Machinery | 2022
43047 Endnote
Autor*innen:
Ciordas-Hertel, George-Petru; Biedermann, Daniel; Winter, Marc; Mordel, Julia; Drachsler, Hendrik
Titel:
How can interaction data be contextualized with mobile sensing to enhance learning engagement assessment in distance learning?
Aus:
Tumuluri, Raj; Sebe, Nicu; Pingali, Gopal; Jayagopi, Dinesh Babu; Dhall, Abhinav; Singh, Richa; Anthony, Lisa; Ali Salah, Albert (Hrsg.): ICMI '22 companion: Companion publication of the 2022 International Conference on Multimodal Interaction, New York; NY: Association for Computing Machinery, 2022 , S. 105-112
DOI:
10.1145/3536220.3558037
URL:
https://dl.acm.org/doi/10.1145/3536220.3558037
Dokumenttyp:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache:
Englisch
Abstract:
Multimodal learning analytics can enrich interaction data with contextual information through mobile sensing. Information about, for example, the physical environment, movement, physiological signals, or smart wearable usage. Through the use of smart wearables, contextual information can thus be captured and made available again to students in further processing steps so that they can reflect and annotate it. This paper describes a software infrastructure and a study design that successfully captured contextual information utilizing mobile sensing using students' smart wearables in distance learning. In the conducted study, data was collected from the smartphones of 76 students as they self-directedly participated in an online learning unit using a learning management system (LMS) over a two-week period. During the students' active phases in the LMS, interaction data as well as state and trait measurements were collected by the LMS. Simultaneously, hardware sensor data, app usage data, interaction with notifications, and ecological momentary assessments (EMA) were automatically but transparently collected from the students' smartphones. Finally, this paper describes some preliminary insights from the study process and their implications for further data processing. (DIPF/Orig.)
DIPF-Abteilung:
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