Voor dit boekje ‘(Her)ken je student!’ hebben studenten en medewerkers hun verhaal verteld over vier verschillende studenttypes, ingedeeld op basis van bevlogenheid en emotionele uitputting. Deze vier types hebben hun eigen karaktereigenschappen en behoeftes. Natuurlijk is iedere student uniek en is geen student precies hetzelfde. Maar dat maakt het ook ongrijpbaar. Want hoe ga je dan om met alle verschillende behoeftes van de honderdduizenden studenten die alleen al in Nederland studeren? De vier herkenbare studenttypes in dit boekje geven richting en bewustwording voor zowel studenten als docenten. Daarnaast worden in dit boekje praktische handvatten aangeboden. Zo kan je als student zelf testen hoe het staat met je eigen bevlogenheid en uitputting. En docenten kunnen de gesprekstips gebruiken om te onderzoeken wat de behoeftes zijn van de student en wat nodig is om deze te kunnen vervullen.
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Hoe ziet een leven lang nieuwsgierig eruit? In een reeks portretten genaamd Nieuwsgierige Types wordt een gezicht gegeven aan nieuwsgierigheid, ondernemendheid, informeel en non-formeel leren. Ter voorbereiding van een nog te publiceren boek over nieuwsgierigheid worden personen geïnterviewd van verschillende achtergronden en leeftijden over hun nieuwsgierigheid, fascinaties en hoe deze bijdragen aan hun ondernemendheid.
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Earlier research argues that educational programmes based on social cognitive theory are successful in improving students’ self-efficacy. Focusing on some formative assessment characteristics, this qualitative research intends to study in-depth how student teachers’ assessment experiences contribute to their self-efficacy. We interviewed 15 second year student teachers enrolled in a competence based teacher educational programme. Thematic content analysis results reveal that the assessment characteristics ‘authenticity’ and ‘feedback’ exert a positive influence on student teachers self-efficacy during all phases of the portfolio competence assessment. The results provide a fine-grained view of several types of self-efficacy information connected with these assessment phases.
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At the beginning of May 2020 Inholland students received an invitation to participate in a large international study on the corona crisis impact on student life and studies. Almost 3000 students participated. This factsheet shows data on their lifestyleand their resilience. But also on their worries about corona, their knowledge of it and their opinion on the information supply.
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In redesigning its curriculum and learning environment, the HU Business School focuses on improving student engagement. In its turn, this should improve the academic success rates. Moreover, challenging honours students in regular courses is also an aim of the redesign. With this in mind, we developed a pilot course in which students are offered five different options of coaching and tuition from the lecturer. This approach was called “The tuition Pentagon”. The five options are designed to match different levels of motivation, competence and ambition. Students reflect on their motivation, competence and ambition and choose their preferred option. An option with extra assignments offers a challenge for honours students.
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A decline in both student well-being and engagement were reported during the COVID-pandemic. Stressors and internal energy sources can co-exist or be both absent, which might cohere with different student needs. This study aimed to develop student profiles on emotional exhaustion and engagement, as well as examine how profiles relate to student participation, academic performance, and overall well-being. Survey-data from 1,460 Dutch higher education students were analyzed and resulted in a quadrant model containing four student profiles on engagement and emotional exhaustion scores. Semi-structured interviews with 13 students and 10 teaching staff members were conducted to validate and further describe the student profiles. The majority of the survey participants were disengaged-exhausted (48%) followed by engaged-exhausted students (29%). Overall, the engagedenergized students performed best academically and had the highest levels of well-being and participation, although engaged-exhausted students were more active in extracurricular activities. The engaged exhausted students also experienced the most pressure to succeed. The qualitative validation of the student profiles demonstrates that students and teachers recognize and associate the profiles with themselves or other students. Changes in the profiles are attributed to internal and external factors, suggesting that they are not fixed but can be influenced by various factors. The practical relevance of the quadrant model is acknowledged by students and teachers and they shared experiences and tips, with potential applications in recognizing students’ well-being and providing appropriate support. This study enriches our grasp of student engagement and well-being in higher education, providing valuable insights for educational practices.
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In this article I will discuss theories on students’ success in higher education and the need for adjustments of these theories in the contemporary, information and media saturated world. The integration theory on student retention, founded by Tinto and further developed by him and many others, lies at the base of most studies on student success. In line with Tinto’s theory the majority of studies measure both social and academic integration of a student, alongside background variables. Social integration is shaped by the personal contact with fellow students and staff and whether or not a student enjoys being at the institute. Academic integration has more to do with academic achievement and sharing the academic norms and values. Although the distinction of these types of integration has been experienced as an artificial one and has been abandoned in more recent studies, the conclusion of most studies remains the same: the higher the level of integration, the greater the level of commitment, which in turn has a positive affect on the likelihood of student persistence in college and the success of a student. More recent studies use ‘engagement’ to embed the various factors of integration to avoid the rigid distinction between social and academic and to include new forms of communication between students for social, academic and other purposes. Furthermore the world has changed since the origin of Tinto’s integration theory in the early eighties, especially if you look at the changes in society under the influence of technology in general and in particular the Internet. New ways of communicating has emerged which brought along new possibilities. The emergence of smart phones has played a big part in the various ways we communicate. The new devices and communication tools have made it possible to employ integrating social and academic activities without the necessity of physical presence. The central question of the article is: Should online communities or engaging platforms like Facebook, be taken into account when investigating the influential facors of student success?
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The purpose of this study was to provide insight into the interplay between student perceptions of competence-based assessment and student self-efficacy, and how this influences student learning outcomes. Results reveal that student perceptions of the form authenticity aspect and the quality feedback aspect of assessment do predict student self-efficacy, confirming the role of mastery experiences and social persuasions in enhancing student self-efficacy as stated by social cognitive theory. Findings do not confirm mastery experiences as being a stronger source of self-efficacy information than social persuasions. Study results confirm the predictive role of students’ self-efficacy on their competence outcomes. Mediation analysis results indicate that student’s perceptions of assessment have an indirect effect on student’s competence evaluation outcomes through student’s self-efficacy. Study findings highlight which assessment characteristics, positively influencing students’ learning, contribute to the effectiveness of competence-based education. Limitations of the study and directions for future research are indicated.
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Learning is all about feedback. Runners, for example, use apps like the RunKeeper. Research shows that apps like that enhance engagement and results. And people think it is fun. The essence being that the behavior of the runner is tracked and communicated back to the runner in a dashboard. We wondered if you can reach the same positive effect if you had a dashboard for Study-behaviour. For students. And what should you measure, track and communicate? We wondered if we could translate the Quantified Self Movement into a Quantified Student. So, together with students, professors and companies we started designing & building Quantified Student Apps. Apps that were measuring all kinds of study-behaviour related data. Things like Time On Campus, Time Online, Sleep, Exercise, Galvanic Skin Response, Study Results and so on. We developed tools to create study – information and prototyped the Apps with groups of student. At the same time we created a Big Data Lake and did a lot of Privacy research. The Big Difference between the Quantified Student Program and Learning Analytics is that we only present the data to the student. It is his/her data! It is his/her decision to act on it or not. The Quantified Student Apps are designed as a Big Mother never a Big Brother. The project has just started. But we already designed, created and learned a lot. 1. We designed and build for groups of prototypes for Study behavior Apps: a. Apps that measure sleep & exercise and compare it to study results, like MyRhytm; b. Apps that measure study hours and compare it to study results, like Nomi; c. Apps that measure group behavior and signal problems, like Groupmotion; d. Apps that measure on campus time and compare it with peers, like workhorse; 2. We researched student fysics to see if we could find his personal Cup-A-Soup-Moment (meaning, can we find by looking at his/her biometrics when the concentration levels dip?); 3. We created a Big Data lake with student data and Open Data and are looking for correlation and causality there. We already found some interesting patterns. In doing so we learned a lot. We learned it is often hard to acquire the right data. It is hard to create and App or a solution that is presenting the data in the right way and presents it in a form of actionable information. We learned that health trackers are still very inprecise. We learned about (and solved some) challenges surrounding privacy. Next year (2017) we will scale the most promising prototype, measure the effects, start a new researchproject and continu working on our data lake. Things will be interesting, and we will blog about it on www.quantifiedstudent.nl.
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Obtaining credits, studying for exams, attending classes, engaging with fellow students and lecturers, living alone or with others, and taking part in extra-curricular activities: there is a fair amount for students in higher education to take in. There are also numerous external factors — such as the COVID-19 pandemic and the changing labour and housing market — that affect students. However, students experience these situations differently and deal with them in different ways. How can we ensure that, notwithstanding these stress factors and differences, as many students as possible become and remain engaged and energised? Happier students tend to be more engaged and generally achieve better study results.1 That is why student well-being is also a widely researched and important topic. The search is on for measures to promote student well-being and success. Having a clear idea of how things are going for a student and what they need is a starting point. This booklet helps readers to identify different student profiles and understand what is needed to improve student success. We zoom in on two key aspects of student success: engagement and emotional exhaustion.
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