Evaluation - the educational context

Evaluation comes in many shapes and sizes. It can be as simple and as grounded in day to day work as a clinical teacher refl ecting on a lost teaching opportunity and wondering how to do it better next time or as complex, top down and politically charged as a major government led evaluation of use of teaching funds with the subtext of re-allocating them. Despite these multiple spectra of scale, perceived ownership, fi nancial and political implications, the underlying principles of evaluation are remarkably consistent. To evaluate well, it needs to be clear who is evaluating what and why. From this will come notions of how it needs to be done to ensure the evaluation is meaningful and useful. This paper seeks to illustrate what evaluation is, why it matters, where to start if you want to do it and how to deal with evaluation that is external and imposed

NPS Customer Loyalty Analysis and Proposals for its Strengthening

Tato diplomová práce je zaměřená na možnosti posílení loajality zákazníků společnosti Atlas Copco Compressor Technique. Teoretická část objasňuje pojmy jako marketingový výzkum, dotazník, zákazník či loajalita. Závěr první části je věnován modelu Net Promoter Score, programu, který je také použit k vypracování samotné analýzy součastné spokojenosti a loajality zákazníků. Výsledky z této analýzy spolu s pozorováním, které autor v podniku provedl, slouží v závěrečné části práce k návrhům, které by měly mít za následek zvýšení počtu loajálních zákazníků této společnosti.This master thesis is focused on possibilities how to strengthen customer loyalty in the company Atlas Copco Compressor Technique. The theoretical part clarifies terms such as marketing research, questionnaire, customer or loyalty. On a later stage it explains the Net Promoter Score, a customer loyalty metric which is also used to conduct the analysis of current customer satisfaction and loyalty itself. Based on the analysis as well as observations from the company gives the author proposals that should result in more loyal customers.

Identifying cross country skiing techniques using power meters in ski poles

Power meters are becoming a widely used tool for measuring training and racing effort in cycling, and are now spreading also to other sports. This means that increasing volumes of data can be collected from athletes, with the aim of helping coaches and athletes analyse and understanding training load, racing efforts, technique etc. In this project, we have collaborated with Skisens AB, a company producing handles for cross country ski poles equipped with power meters. We have conducted a pilot study in the use of machine learning techniques on data from Skisens poles to identify which "gear" a skier is using (double poling or gears 2-4 in skating), based only on the sensor data from the ski poles. The dataset for this pilot study contained labelled time-series data from three individual skiers using four different gears recorded in varied locations and varied terrain. We systematically evaluated a number of machine learning techniques based on neural networks with best results obtained by a LSTM network (accuracy of 95% correctly classified strokes), when a subset of data from all three skiers was used for training. As expected, accuracy dropped to 78% when the model was trained on data from only two skiers and tested on the third. To achieve better generalisation to individuals not appearing in the training set more data is required, which is ongoing work.Comment: Presented at the Norwegian Artificial Intelligence Symposium 201

Information Outlook, September 2000

Volume 4, Issue 9https://scholarworks.sjsu.edu/sla_io_2000/1008/thumbnail.jp

Outlook Magazine, Autumn 2014

https://digitalcommons.wustl.edu/outlook/1193/thumbnail.jp

Digital Subjectivation and Financial Markets: Criticizing Social Studies of Finance with Lazzarato

The recently rising field of Critical Data Studies is still facing fundamental questions. Among these is the enigma of digital subjectivation. Who are the subjects of Big Data? A field where this question is particularly pressing is finance. Since the 1990s traders have been steadily integrated into computerized data assemblages, which calls for an ontology that eliminates the distinction between human sovereign subjects and non-human instrumental objects. The latter subjectivize traders in pre-conscious ways, because human consciousness runs too slow to follow the volatility of the market. In response to this conundrum Social Studies of Finance has drawn on Actor-Network Theory to interpret financial markets as technically constructed networks of human and non-human actors. I argue that in order to develop an explicitly critical data study it might be advantageous to refer to Maurizio Lazzarato’s theory of machinic subjugation instead. Although both accounts describe financial digital subjectivation similarly, Lazzarato has the advantage of coupling his description to a clear critique of and resistance to finance