Eva Ritz

Eva Ritz

Last Name

Ritz

First name

Eva

Email

eva.ritz@unisg.ch

ORCID

0000-0002-2077-3786

Now showing 1 - 10 of 11

How to Support Students’ Self-Regulated Learning in Times of Crisis: An Embedded Technology-Based Intervention in Blended Learning Pedagogies

( 2023-09-22)
Eva Ritz
;
Roman Rietsche
;
Jan Marco Leimeister

With the increasing prevalence of technology-enhanced learning environments, self-regulated learning (SRL) has become a crucial skill for management students and graduates in the 21st century. Self-regulated learners can take control of their own learning process by setting learning objectives and selecting appropriate learning strategies. As a result of the recent COVID-19 crisis, universities were compelled to shift to online course delivery, which greatly reduced social interaction between educators and learners and challenged educators’ feedback practices. To address this issue, we developed and embedded a technology-based intervention with temporal-proximate and regular formative feedback assessments in a large-scale management course to promote graduate students’ SRL practices. We evaluated the intervention in a quasi-experiment, which found that students with the embedded SRL intervention had higher self-assessment and learning outcome scores and lower absolute self-assessment deviation. Our study makes at least three contributions. First, we shed light on students’ SRL strategies in times of emergency remote learning, highlighting their extensive need for social support and comparison. Second, we extend the literature on SRL and social-cognitive theory by unveiling a hidden effect when embedding temporal-proximate and regular interventions. Third, we contribute an empirically evaluated intervention to foster students’ SRL in blended learning and online pedagogies.

Type: journal article

Journal: Academy of Management Learning & Education (AMLE)

Volume: 22

Issue: 3

URL: https://journals.aom.org/doi/full/10.5465/amle.2022.0188

DOI: 10.5465/amle.2022.0188

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/118210

Scopus© Citations 4
BALANCING BYTES WITH BRAINS: EXPLORING THE ROLE OF LEARNERS' CONTROL IN PERSONALIZED LEARNING TASKS

( 2024)
Eva Ritz

The increasing prevalence of artificial intelligence (AI)-based learning systems unleashes new potentials in designing personalized learning experiences that enhance learning outcomes. However, prior research indicates that such systems can negatively impact engagement due to issues in human information processing. This study examines whether giving learners control over task difficulty selection in personalized learning systems can mitigate these effects. A laboratory within-subjects experiment involving 80 participants explored how control over personalized vocabulary learning affects learning performance and autonomy satisfaction. As such a control feature may lead to deeper information processing, I investigate the mediating effect of cognitive workload on the main effect. The study aims to contribute to human-AI interaction literature by shedding light on the importance of control in personalized system design and investigating its effects on cognitive workload, overall task performance, and autonomy satisfaction.

Type: conference paper

Journal: European Conference on Information Systems (ECIS)

DOI: Balancing Bytes with Brains: Exploring the Role of Learners' Control in Personalized Learning Tasks

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/119944
What to Learn Next? Designing Personalized Learning Paths for Re-&Upskilling in Organizations

( 2023-01-06)
Eva Ritz
;
Leonie Freise
;
Edona Elshan
;
Roman Rietsche
;
Ulrich Bretschneider

The fast-paced acceleration of digitalization requires extensive re-&upskilling, impacting a significant proportion of jobs worldwide. Technology-mediated learning platforms have become instrumental in addressing these efforts, as they can analyze platform data to provide personalized learning journeys. Such personalization is expected to increase employees’ empowerment, job satisfaction, and learning outcomes. However, the challenge lies in efficiently deploying these opportunities using novel technologies, prompting questions about the design and analysis of generating personalized learning paths in organizational learning. We, therefore, analyze and classify recent research on personalized learning paths into four major concepts (learning context, data, interface, and adaptation) with ten dimensions and 34 characteristics. Six expert interviews validate the taxonomy’s use and outline three exemplary use cases, undermining its feasibility. Information Systems researchers can use our taxonomy to develop theoretical models to study the effectiveness of personalized learning paths in intra-organizational re-&upskilling.

Type: conference paper

Journal: Hawaii International Conference on System Sciences (HICSS)

URL: https://hdl.handle.net/10125/106406

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/118212
GETTING INTO FLOW!? ENHANCE FLOW-LIKE EXPERIENCES AND LEARNING PERFORMANCE THROUGH PERSONALIZED LEARNING ACTIVITIES

( 2023-06)
Ritz, Eva

Although intelligent learning systems provide new opportunities for personalizing learning activities, important design questions remain. To unleash the full impact of such systems, it is vital to examine how the use of Bayesian knowledge tracing can provide learners personalized learning activities and shape their flow experience, performance, and continuity intention. Further, this study explores the moderating role of a growth mindset on the relation between learning task adaptation and flow experience. I rely on electroencephalography to increase the internal validity of flow measurements. The study builds on Flow Theory and aims to empirically unveil the influence of an intelligent personalization of learning processes. The next step will be an experiment with 80 participants following the developed experimental design to evaluate flow experiences in intelligent learning systems. The results of this experiment aim to guide educational designers with prescriptive knowledge on how to design flow-like learning experiences in intelligent learning systems.

Type: conference paper

Journal: European Conference on Information Systems (ECIS)

URL: https://aisel.aisnet.org/ecis2023_rip/81/

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/116332
Artificial Socialization? How Artificial Intelligence Applications Can Shape A New Era of Employee Onboarding Practices

( 2023-01-06)
Ritz, Eva
;
Fabio, Donisi
;
Elshan, Edona
;
Rietsche, Roman

Onboarding has always emphasized personal contact with new employees. Excellent onboarding can extend employee retention and improve loyalty. Even in a physical setting, the onboarding process is demanding for both the newcomer and the onboarding organization. Remote work, in contrast, has made this process even more challenging by forcing a rapid shift from offline to online onboarding practices. Organizations are adopting new technologies like artificial intelligence (AI) to support work processes, such as hiring processes or innovation facilitation, which could shape a new era of work practices. However, it has not been studied how AI applications can or should support onboarding. Therefore, our research conducts a literature review on current onboarding practices and uses expert interviews to evaluate AI's potential and pitfalls for each action. We contribute to the literature by presenting a holistic picture of onboarding practices and assessing potential application areas of AI in the onboarding process.

Type: conference paper

Journal: Hawaii International Conference on System Sciences (HICSS)

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/107805
A Corpus for Suggestion Mining of German Peer Feedback

( 2022)
Rietsche, Roman
;
Ritz, Eva
;
Janda, Julius
;
Pfütze, Dominik

Peer feedback in online education becomes increasingly important to meet the demand for feedback in large scale classes, such as e.g. Massive Open Online Courses (MOOCs). However, students are often not experts in how to write helpful feedback to their fellow students. In this paper, we introduce a corpus compiled from university students’ peer feedback to be able to detect suggestions on how to improve the students’ work and therefore being able to capture peer feedback helpfulness. To the best of our knowledge, this corpus is the first student peer feedback corpus in German which additionally was labelled with a new annotation scheme. The corpus consists of more than 600 written feedback (about 7,500 sentences). The utilisation of the corpus is broadly ranged from Dependency Parsing to Sentiment Analysis to Suggestion Mining, etc. We applied the latter to empirically validate the utility of the new corpus. Suggestion Mining is the extraction of sentences that contain suggestions from unstructured text. In this paper, we present a new annotation scheme to label sentences for Suggestion Mining. Two independent annotators labelled the corpus and achieved an inter-annotator agreement of 0.71. With the help of an expert arbitrator a gold standard was created. An automatic classification using BERT achieved an accuracy of 75.3%.

Type: conference paper

Journal: Language Resources and Evaluation Conference (LREC)

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/109467
Unleashing Process Mining for Education: Designing an IT-Tool for Students to Self-Monitor their Personal Learning Paths

( 2022-02-23)
Ritz, Eva
;
Wambsganss, Thiemo
;
Rietsche, Roman
;
Schmitt, Anuschka
;
Oeste-Reiß, Sarah
;
Leimeister, Jan Marco

The ability of students to self-monitor their learning paths is in demand as never before due to the recent rise of online education formats, which entails less interaction with lecturers. Recent advantages in educational process mining (EPM) offer new opportunities to monitor students’ learning paths by processing log data captured by technology-mediated learning environments. However, current literature falls short on providing user-centered design principles for IT-tools which can monitor learning paths using EPM. Hence, in this paper, we examine how to design a self-monitoring tool that supports students to evaluate their learning paths. Based on theoretical insights of 66 papers and nine user interviews, we propose seven design principles for an IT-tool which facilitates self-monitoring for students based on EPM. Further, we evaluate the design principles with seven potential users. Our results demonstrate a promising approach to help students improve their self-efficacy in their individual learning process using EPM.

Type: conference paper

Journal: Internationale Tagung Wirtschaftsinformatik (WI)

URL: https://aisel.aisnet.org/wi2022/digital_education/digital_education/6/

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/108942
Learn Smarter, Not Harder – Exploring the Development of Learning Analytics Use Cases to Create Tailor-Made Online Learning Experiences

( 2021)
Ritz, Eva
;
Grüneke, Timo

Our world is significantly shaped by digitalization, fostering new opportunities for technology-mediated learning. Therefore, massive amounts of knowledge become available online. However, concurrently these formats entail less interaction and guidance from lecturers. Thus, learners need to be supported by intelligent learning tools that provide suitable knowledge in a tailored way. In this context, the use of learning analytics in its multifaceted forms is essential. Existing literature shows a proliferation of learning analytics use cases without a systematic structure. Based on a structured literature review of 42 papers we organized existing literature contributions systematically and derived four use cases: learning dashboards, individualized content, tutoring systems, and adaptable learning process based on personality. Our use cases will serve as a basis for a targeted scientific discourse and are valuable orientation for the development of future learning analytics use cases to give rise to the new form of Learning Experience Platforms.

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/111248
Offloading to Digital Minds: How Generative AI Can Help to Craft

( 2024)
Eva Ritz
;
Leonie Rebecca Freise
;
Mahei Manhai Li

In the era of ChatGPT and other generative AI tools, white-collar workers are given tremendous potential to simplify everyday tasks. Within vocational psychology, this phenomenon is known as job crafting. We conduct an electroencephalography-based mixed-factorial experiment to explore the underlying mechanisms of how and why the use of generative AI tools can lead to job crafting. Relying on cognitive load theory and resource demand theory, we measure the effects of ChatGPT use and prompt engineering guidance in strategic thinking tasks. We hypothesize that individuals who use ChatGPT without and with prompting examples rely on cognitive offloading to avoid cognitive effort, affecting resource demands. An initial evaluation of our experiment task design provides promising results. We plan our experiment with participants who are familiar with executive assistant tasks. Our expected results contribute to the ongoing discussion of ICT-enabled job crafting and provide empirical-driven explanations of AI-enabled job crafting mechanisms.

Type: book section

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/120390
How a Swiss luxury retailer implements process mining to improve data-driven customer excellence

( 2024)
Eva Ritz
;
Adrian Joas
;
Thiemo Wambsganss
;
Roman Rietsche
;
Jan Marco Leimeister

In today’s digital transformation era, process mining has emerged as a crucial technology, playing an integral part in the digital strategies of many organizations. Despite its significance, implementing process mining to leverage data-driven decision-making and boosting process efficiency presents notable challenges for such companies. This case study delves into the journey of the fictitious Swiss luxury retailer Elysian as they utilize process mining to derive data-driven insights on process inefficiencies and bottlenecks to increase their customer excellence for online retail procurement. The case highlights the capabilities of process mining for organizations. It is among the first to offer students hands-on guidance on process discovery, conformance, and enhancement using real-world data. Students take the role of Lisa Dister, Head of procurement in the business unit home care, who urgently requires improving process transparency after an unsatisfying internal audit result. This immersive experience helps students understand the application of process mining in high-volume data scenarios and equips them with skills in data literacy. Moreover, students are challenged to suggest recommendations for long-term process optimization and reflect on the effectiveness of process mining for tackling procurement issues.

Type: journal-article

Journal: Journal of Information Technology Teaching Cases

DOI: 10.1177/20438869241261399

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/120391

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