The goal of this study was therefore to test the idea that computationally analysing the Fontys National Student Surveys (NSS) open answers using a selection of standard text mining methods (Manning & Schütze 1999) will increase the value of these answers for educational quality assurance. It is expected that human effort and time of analysis will decrease significally. The text data (in Dutch) of several years of Fontys National Student Surveys (2013-2018) was provided to Fontys students of the minor Applied Data Science. The results of the analysis were to include topic and sentiment modelling across multiple years of survey data. Comparing multiple years was necessary to capture and visualize any trends that a human investigator may have missed while analysing the data by hand. During data cleaning all stop words and punctuation were removed, all text was brought to a lower case, names and inappropriate language – such as swear words – were deleted. About 80% of 24.000 records were manually labelled with sentiment; reminder was used for algorithms’ validation. In the following step a machine learning analysis steps: training, testing, outcomes analysis and visualisation, for a better text comprehension, were executed. Students aimed to improve classification accuracy by applying multiple sentiment analysis algorithms and topics modelling methods. The models were chosen arbitrarily, with a preference for a low complexity of a model. For reproducibility of our study open source tooling was used. One of these tools was based on Latent Dirichlet allocation (LDA). LDA is a generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar (Blei, Ng & Jordan, 2003). For topic modelling the Gensim (Řehůřek, 2011) method was used. Gensim is an open-source vector space modelling and topic modelling toolkit implemented in Python. In addition, we recognized the absence of pretrained models for Dutch language. To complete our prototype a simple user interface was created in Python. This final step integrated our automated text analysis with visualisations of sentiments and topics. Remarkably, all extracted topics are related to themes defined by the NSS. This indicates that in general students’ answers are related to topics of interest for educational institutions. The extracted list of the words related to the topic is also relevant to this topic. Despite the fact that most of the results require further human expert interpretation, it is indicative to conclude that the computational analysis of the texts from the open questions of the NSS contain information which enriches the results of standard quantitative analysis of the NSS.
During the past two decades the implementation and adoption of information technology has rapidly increased. As a consequence the way businesses operate has changed dramatically. For example, the amount of data has grown exponentially. Companies are looking for ways to use this data to add value to their business. This has implications for the manner in which (financial) governance needs to be organized. The main purpose of this study is to obtain insight in the changing role of controllers in order to add value to the business by means of data analytics. To answer the research question a literature study was performed to establish a theoretical foundation concerning data analytics and its potential use. Second, nineteen interviews were conducted with controllers, data scientists and academics in the financial domain. Thirdly, a focus group with experts was organized in which additional data were gathered. Based on the literature study and the participants responses it is clear that the challenge of the data explosion consist of converting data into information, knowledge and meaningful insights to support decision-making processes. Performing data analyses enables the controller to support rational decision making to complement the intuitive decision making by (senior) management. In this way, the controller has the opportunity to be in the lead of the information provision within an organization. However, controllers need to have more advanced data science and statistic competences to be able to provide management with effective analysis. Specifically, we found that an important skill regarding statistics is the visualization and communication of statistical analysis. This is needed for controllers in order to grow in their role as business partner..
Art therapy is widely used and effective in the treatment of patients diagnosed with Personality Disorders (PDs). Current psychotherapeutic approaches may benefit from this additional therapy to improve their efficacy. But what is the patient perspective upon this therapy? This study explored perceived benefits of art therapy for patients with PDs to let the valuable perspective of patients be taken into account. Using a quantitative survey study over 3 months (N = 528), GLM repeated measures and overall hierarchical regression analyses showed that the majority of the patients reported quite a lot of benefit from art therapy (mean 3.70 on a 5-point Likert scale), primarily in emotional and social functioning. The improvements are concentrated in specific target goals of which the five highest scoring goals affected were: expression of emotions, improved (more stable/positive) self-image, making own choices/autonomy, recognition of, insight in, and changing of personal patterns of feelings, behaviors and thoughts and dealing with own limitations and/or vulnerability. Patients made it clear that they perceived these target areas as having been affected by art therapy and said so at both moments in time, with a higher score after 3 months. The extent of the perceived benefits is highly dependent for patients on factors such as a non-judgmental attitude on the part of the therapist, feeling that they are taken seriously, being given sufficient freedom of expression but at the same time being offered sufficient structure and an adequate basis. Age, gender, and diagnosis cluster did not predict the magnitude of perceived benefits. Art therapy provides equal advantages to a broad target group, and so this form of therapy can be broadly indicated. The experienced benefits and the increase over time was primarily associated with the degree to which patients perceive that they can give meaningful expression to feelings in their artwork. This provides an indication for the extent of the benefits a person can experience and can also serve as a clear guiding principle for interventions by the art therapist.
Plastic waste is one of the largest environmental problems in the 21st century. By 2050, up to 12,000 Mt of plastic waste is estimated to be in landfills or in the natural environment. Biochemical recycling by using modified microbial enzymes have shown potentials in the back-to-monomer (BTM) recycling of polyethylene terephthalate by breaking down the polymers into re-usable monomers. These enzymes can be produced via fungal species. In order to make this biochemical BTM process viable a process integrated enzyme production is key in increasing the efficiency and reducing the cost of enzymes. For this a molecular monitoring method, such as RNA-seq (RNA-sequencing), is needed. RNA-seq can achieve a snapshot on enzyme producing process inside of the cell by semi-quantitatively measuring the volume of enzyme encoding RNAs. This information can bring hints on fungal strain improvement by promoting the desired enzymes. It also helps to instantly monitor the BTM production outcomes. However, conventional RNA-seq platforms can only be performed via service providers or startup investments reaching 2 million euros. Each round of analysis could take as long as 6 weeks turnaround time. Furthermore, the method creates huge amount of complicated datasets, only by expert skills and specialized high performance computing the data can be sorted in a comprehensive manner. To solve these problems, in this project, by combining the expertise on plastic end-of-life control, fungal enzyme production, molecular monitoring and Bioinformatics from both the UAS and SME sides, we aim to implement a novel RNA-seq based system to monitor the in-process enzyme production for plastic degradation. We will optimize the existing portable RNA-seq prototype machinery for semi-real time monitoring of the BTM recycling process. The downstream data will be handled by a tailored analysis pipeline designed with expert knowledge via an user-friendly interface.
Circular agriculture is an excellent principle, but much work needs to be done before it can become common practice in the equine sector. In the Netherlands, diversification in this sector is growing, and the professional equine field is facing increasing pressure to demonstrate environmentally sound horse feeding management practices and horse owners are becoming more aware of the need to manage their horses and the land on which they live in a sustainable manner. Horses should be provided with a predominantly fibre-based diet in order to mimic their natural feeding pattern, however grazing impacts pasture differently, with a risk of overgrazing and soil erosion in equine pastures. Additionally, most horses receive supplements not only with concentrates and oils, but also with minerals. Though the excess minerals are excreted in the manure of horses, these minerals can accumulate in the soil or leach to nearby waterways and pollute water resources. Therefore, the postdoc research aims to answer the main question, “What horse feeding practices and measurements are needed to reduce and prevent environmental pollution in the Netherlands?” The postdoc research is composed of two components; a broad survey-based study which will generate quantitative data on horse feeding management and will also obtain qualitative data on the owners’ engagement or willingness of horse owners to act sustainably. Secondly, a field study will involve the collection of detailed data via visits to horse stables in order to gather data for nutritional analysis and to collect fecal samples for mineral analysis. Students, lecturers and partners will actively participate in all phases of the planned research. This postdoc research facilitates learning and intends to develop a footprint calculator for sustainable horse feeding to encompass the complexity of the equine sector, and to improve the Equine Sports and Business curriculum.
