At the beginning of May 2020 all Inholland-students received an invitation to participate in a large international study on the corona crisis impact on student life and studies. This poster, presented by the Study Success Research Group, covers relevant results divided in four themes. These themes are student wellbeing, student engagement, satisfaction and the coronavirus. To determine student wellbeing we asked students about their feelings and contacts. Student engagement is phrased in time allocation and engagement. We also wanted to find out how satisfied students were with things like ICT facilities, quality of education and provision of information. Of course we asked students about (not) having corona and adhering to the measures.
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For my PhD research I build a structural model to predict student success. Initially to show the influence of social media use by first year students in higher education. However, for this research I use the model to investigate the predictive value of a student choice test. This test is mandatory for all students prior to their enrolment at the Amsterdam University of Applied Sciences. In this study two of the Institutes (Communication and Creative Business/Media, Information and Communication) of the Faculty of Digital Media and the Creative Industries participated with a first year enrollment in the year 2017 of 1010 students (respectively of 327 and 683), and in 2018, 1193 students (respectively 225 and 968). This study choice test involved an assignment that the student-to-be had to do at home and bring to the Institute when they took part in the second half of the study choice test. This second half involved an exam in topics central to the curriculum, a Dutch language test and all students had a final meeting with a teacher where they were given a positive or negative advice. Because of the large number of students, a substantial number of teachers and resources were used for this test. In order to see the pros and cons of the test, the predictive value was tested along with other variables which are proven to have a predictive value on student success. The best proven variables from Tinto’s theory were included, based on previous studies. The central variable in Tinto’s study is ‘satisfaction’ (which in other research is revert to as ‘engagement’ of ‘belonging’), consisting originally of a vast number of manifest variables. By using a fraction of those variables, I simplified the model, so it was an easier tool to use for teachers and management and in the meantime, avoiding the capitalization of chance. The smaller latent variable ‘satisfaction’ was tested using principal component analysis to prove the manifest variables where in fact representing one latent variable. Cronbach’s alpha and Guttman’s lambda-2 then provided the internal consistency and reliability of the variable. Along with ‘satisfaction’, the model included different background variables (gender, prior education, ethnicity), commitment and effort, expected progress and of course study success. This was measured by the time it takes a student to finish all first year exams and the average grade point (GPA). SPSS AMOS was used for testing the fit of the model and showed reasonable values for the normed fit index (NFI), the comparative fit index (CFI), the Tucker-Lewis Index (TLI) and the root mean square error of approximation (RMSEA). The advice from the study choice test and the scores were tested in the model to uncover if there was a significant difference. Furthermore, the influence of all variables in the model were compared for their influence on study success.
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Student satisfaction gains an increasingly central position in the context of quality measurements. However, student satisfaction can also be stipulated as an important motivational factor for students as learners. This study combines this perspective on student satisfaction with the notion of differences in students’ ability. We hypothesize that differences in ability result in differences in student satisfaction. In line with concepts of high ability education, it is additionally hypothesized that this relation is mediated by educational stimulation - divided in cognitive, creative and professional stimulation – as well as by participation in honours programs. A structural equation modelling (N=733) of factors affecting student satisfaction in higher education shows that cognitive, creative and professional stimulation are the largest influencers of bachelor students’ sense of satisfaction. The interrelation between these three aspects of educational stimulation also shows the complexity of higher educational practice, since it suggests that cognitive stimulation cannot be realized without a creative factor, and vice versa. Professional stimulation needs both. Furthermore, the results show that educational stimulation mediates the effect of students’ ability on their educational satisfaction. This implies that changes in education can indeed influence students’ educational satisfaction, especially by providing educational quality. Finally, considering students’ ability level, it is shown that especially cognitive abler students are less easy to satisfy. The combination of educational stimulation and ability suggests that especially the more cognitive able students do not feel themselves sufficiently cognitively or creatively stimulated, and hence are less satisfied in vocational higher education.
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How are the students of Inholland University of Applied Sciences doing? How do students assess their health and how engaged are they? What are the biggest stressors during their time as a student and what stress reactions do they experience? How resilient and optimistic are the students, and from whom do they get the necessary support? Based on the Student WellBeing Model, this fact sheet shows the most important results of the Student Well-Being Study 2017–2018. The questionnaire was completed by students in the classroom (n=407).
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As part of my PhD research, I investigate the influence of the use of social media by first year students in higher education. In this research I have lessened the amount of variables, from Tinto’s theory, by including only the best-proven predictive variables, based on previous studies. Hereby, avoiding the capitalization of chance and a more easy to use model for teachers and management has been built. The latent variable ‘satisfaction’ is constructed by using just a fraction of the original manifest variables and tested using principal component analysis to proof the model can be simplified. Furthermore, I enriched the model with the use of social media, in particular Facebook, to better suit students’ contemporary society in the developed world. With principal analysis on Facebook usage, I measured the purpose of Facebook use (information, education, social and leisure) and the use of different pages amongst students. This provided different integration/engagement components, which are also included in the simplified model. For the principal component-analysis, Cronbach’s alpha and Guttman’s lambda-2 showed internal consistency and reliability. SPSS AMOS was used for testing the fit of the model and showed reasonable values for the normed fit index (NFI), the comparative fit index (CFI), the Tucker-Lewis Index (TLI) and the root mean square error of approximation (RMSEA). This study will compare different background variables with the model to uncover the possible influences upon student success, engagement/satisfaction and social media use. Ultimately this paper will provide a better insight into what kind of influence social media can have upon student success.
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Increasing students’ motivation in higher education by designing a specific curriculum has always been a challenging but very complex process. The Department of Business, Finance and Marketing (BFM) of The Hague University of Applied Sciences (THUAS) initiated a redesign of the curricula with the major goals of increasing flexibility of learning opportunities and offering students a more motivating, inspiring and richer diversity of learning experiences. In the literature of learning in higher education this has often been labeled as ‘offering extracurricular learning opportunities’. The redesign of the curriculum implies that the new one will result in an enhancement of the flexibility of the curriculum, by offering learning opportunities beyond the borders of specific programs like marketing, finance or entrepreneurship and retail management. The richness and diversity should create flexible platforms, offering students the possibility to enrich their career choices to design their own personalised career path, hopefully maximizing the possibilities for their talent development. However, very little is known about the relationship between the students’ satisfaction with extracurricular learning opportunities, aiming at the personalisation of students’ career choices, and their motivation. In this chapter we describe our research into this relationship between student motivation and learning environments. Designing a network curriculum by increasing the possibility of extracurricular learning opportunities in higher education could have a positive impact on students’ motivation when it is combined with activities to increase goal students’ commitment. This depends on teachers’ qualities to communicate the valence and instrumentality of the learning possibilities offered for the prospective work environment. This is a complex issue however. Teachers from different educational programs, even in the same domain, have a different orientation on existing learning opportunities within one specific program. Excellent coaching skills by tutors are important. These coaching skills are necessary to support students in the process of envisioning extracurricular learning opportunities when important career choices have to be made.
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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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The corona pandemic has forced higher education (HE) institutes to transition to online learning, with subsequent implications for student wellbeing. Aims: This study explored influences on student wellbeing throughout the first wave of the corona crisis in the Netherlands by testing serial mediation models of the relationships between perceived academic stress, depression, resilience, and HE support.
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Author-supplied abstract: Developing large-scale complex systems in student projects is not common, due to various constraints like available time, student team sizes, or maximal complexity. However, we succeeded to design a project that was of high complexity and comparable to real world projects. The execution of the project and the results were both successful in terms of quality, scope, and student/teacher satisfaction. In this experience report we describe how we combined a variety of principles and properties in the project design and how these have contributed to the success of the project. This might help other educators with setting up student projects of comparable complexity which are similar to real world projects.
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Student success is a critically important concept in educational assessment and research, yet a comprehensive synthesis of its defining elements remains absent. To address this gap, a scoping review was conducted, identifying 274 peer-reviewed studies published between 2011 and 2022. From these studies, data pertaining to conceptualizations of student success and related factors were extracted and analyzed using inductive coding to uncover key themes and recurring patterns. The review culminated in a comprehensive definition of student success, encompassing five core dimensions: persistence and academic progress, academic performance, attainment of learning objectives, satisfaction, and career success. Additionally, four distinct categories of factors related to student success were identified, including background and pre-college experiences, psychosocial capital, educational experiences, and institutional factors. These findings provide grounds for moving beyond traditional narrow interpretations of student success by acknowledging its multidimensional nature. This understanding of student success’ multidimensionality is essential to equip educational institutions in better preparing students to navigate the complexities of contemporary societal challenges, leading to the development of more well-rounded and successful graduates.
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