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Browsing by Subject "keskeyttäminen"

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  • Salminen, Tuukka (2022)
    Aims of the study. This study seeks to find out what kind of situations students typically face during their progress through university studies and what kind of different pathways can be identified as a series of these situations. The aim was to map out and to develop a clustering-based method of identifying these situations and pathways from student transcript data that would complement the information provided by commonly used measures of student progression. Methods. The research strategy of this study follows that of design research, where methods and new knowledge is built iteratively. The data consists of student transcript data of 3167 students at the University of Helsinki who had started their studies in computer science, mathematics, or general and adult education between the years 2010 and 2015. The data was provided by the Agile Education Research group at the University of Helsinki and contained all records of passed or failed completion attempts that had been recorded by 11.3.2020. The data was shaped to coarser level to be used in cluster analysis and clustered using k-medians clustering. Results and conclusions. The results show that it is possible to use clustering as a tool to better understand student transcript data and the pathways students take through their university degrees. The shown clustering makes it possible to describe the progression of studies both on the individual and group levels. Three clusters defining the starting situations and 22 clusters defining the situations during studies were identified. Transitions between clusters show that series of clusters for several pathways that have different stages and outcomes. In conclusion, the results show that student transcript data contains information which universities could use in efforts aimed at helping students advance in their studies
  • Salminen, Tuukka (2022)
    Aims of the study. This study seeks to find out what kind of situations students typically face during their progress through university studies and what kind of different pathways can be identified as a series of these situations. The aim was to map out and to develop a clustering-based method of identifying these situations and pathways from student transcript data that would complement the information provided by commonly used measures of student progression. Methods. The research strategy of this study follows that of design research, where methods and new knowledge is built iteratively. The data consists of student transcript data of 3167 students at the University of Helsinki who had started their studies in computer science, mathematics, or general and adult education between the years 2010 and 2015. The data was provided by the Agile Education Research group at the University of Helsinki and contained all records of passed or failed completion attempts that had been recorded by 11.3.2020. The data was shaped to coarser level to be used in cluster analysis and clustered using k-medians clustering. Results and conclusions. The results show that it is possible to use clustering as a tool to better understand student transcript data and the pathways students take through their university degrees. The shown clustering makes it possible to describe the progression of studies both on the individual and group levels. Three clusters defining the starting situations and 22 clusters defining the situations during studies were identified. Transitions between clusters show that series of clusters for several pathways that have different stages and outcomes. In conclusion, the results show that student transcript data contains information which universities could use in efforts aimed at helping students advance in their studies
  • Grandell, Leena Johanna (2020)
    Aims. Non-attendance reduces the effectiveness of psychotherapies and wastes resources in the health sector. It comprises both treatment refusal and drop-out. This study aims at investigating the association between patients’ psychological suitability to psychotherapy and treatment non-attendance. Methods. The study sample consisted of 326 Finnish adult outpatients suffering from mood or anxiety disorders and participating in the Helsinki Psychotherapy Study (HPS).The patients were randomized in three study groups: solution-focused therapy (n=97, 12 sessions), short (n=101, 20 sessions) and long (n=128, 3 years) psychodynamic therapies. Psychological suitability was measured with Suitability for Psychotherapy Scale (SPS) total score and seven subscores. Refusing the offered therapy after randomization was considered treatment refusal. Drop-out occurred if patient terminated therapy unilaterally before its anticipated length. Statistical analysis were carried out with linear model and Cox model. Results and Conclusions. The risk of treatment refusal was associated with therapy length and highest in long-term psychodynamic psychotherapy, which might be related to the randomization. As expected, poor suitability measured with SPS total score predicted treatment non-attendance. This was most notably seen in case of poor reflective ability, problems in interaction and problematic self-concept in relation to ego ideal. Patients with poor suitability were more likely to drop-out from solution-focused therapy and long psychodynamic therapy than from short psychodynamic therapy.
  • Grandell, Leena Johanna (2020)
    Aims. Non-attendance reduces the effectiveness of psychotherapies and wastes resources in the health sector. It comprises both treatment refusal and drop-out. This study aims at investigating the association between patients’ psychological suitability to psychotherapy and treatment non-attendance. Methods. The study sample consisted of 326 Finnish adult outpatients suffering from mood or anxiety disorders and participating in the Helsinki Psychotherapy Study (HPS).The patients were randomized in three study groups: solution-focused therapy (n=97, 12 sessions), short (n=101, 20 sessions) and long (n=128, 3 years) psychodynamic therapies. Psychological suitability was measured with Suitability for Psychotherapy Scale (SPS) total score and seven subscores. Refusing the offered therapy after randomization was considered treatment refusal. Drop-out occurred if patient terminated therapy unilaterally before its anticipated length. Statistical analysis were carried out with linear model and Cox model. Results and Conclusions. The risk of treatment refusal was associated with therapy length and highest in long-term psychodynamic psychotherapy, which might be related to the randomization. As expected, poor suitability measured with SPS total score predicted treatment non-attendance. This was most notably seen in case of poor reflective ability, problems in interaction and problematic self-concept in relation to ego ideal. Patients with poor suitability were more likely to drop-out from solution-focused therapy and long psychodynamic therapy than from short psychodynamic therapy.