Challenge-Based Learning And Constructive Alignment: A Challenge For Information Systems’ Educators

Challenge-Based Learning (CBL) is an emerging approach to the design of education activities known for its benefits in fostering student engagement and, consequently, positively affecting their learning outcomes. For the educator, the ’challenge in the challenge’ is to guarantee that the CBL-based education design follows certain regulations, like ensuring proper curriculum coverage with Constructive Alignment. This challenge becomes particularly difficult to address in the field of Information Systems, within Computer Science, where multiple practices can be followed to solve the same problem. This is even more challenging when CBL is applied at course-level, where the curriculum of the course focuses on a subset of those practices. This paper targets two central questions for the educators willing to apply CBL while complying with Constructive Alignment in their course design: (1) How to ensure that the results based on solutions designed to address student-defined challenges are successfully aligned to the course’s intended learning outcomes? (2) How to use these results as evidence of learning and as an assessment component? We discuss our experience and lessons learned applying CBL for the redesign and execution of the Smart Industry Systems course of the University of Twente, while ensuring proper curriculum coverage and compliance with Constructive Alignment

[pt] WEARABLES PARA APOIAR A REPRESENTAÇÃO ESPACIAL POR INDIVÍDUOS CEGOS

A dificuldade de locomoção de pedestres cegos é um problema complexo constituído das dificuldades de percepção e de orientação. Parte da dificuldade de percepção é identificar pontos de referência, que é necessário para que indivíduos montem uma representação do espaço, orientem-se nesse espaço e definam trajetórias para se locomover. Nessa pesquisa, foram desenvolvidos e investigados wearables para apoiar indivíduos cegos a identificar pontos de referência. O primeiro Estudo de Caso foi realizado para investigar uma maneira de evitar o masking, problema causado pela tecnologia que consiste numa sobrecarga cognitiva e no prejuízo temporário da capacidade do indivíduo de sensoriar o ambiente com seus sentidos. Para investigar o masking, foram realizados Estudos de Caso com participantes cegos e wearables propostos nessa pesquisa. A partir dos estudos, conclui-se que o wearable dessa pesquisa foi bem sucedido em evitar o masking e essa abordagem foi considerada uma alternativa válida para pesquisadores que investigam esse problema em outros contextos. No segundo Estudo de Caso, já com o masking controlado, concluiu-se que o wearable proposto nessa pesquisa possibilita aos indivíduos cegos explorar mais pontos de referência em relação à exploração exclusivamente com a bengala. Essa pesquisa contribui também com um conjunto de recomendações para projetistas de wearables para mobilidade de cegos.The difficulty in the locomotion of blind pedestrians is a complex problem that comprises the difficulties of perception and orientation. Part of the difficulty of perception is the identification of landmarks, which is necessary for the orientation process and also the acquisition of a spatial representation. The spatial representation will be used later when orientating in this space and for defining paths to move from a given place to another. In this research, wearables were investigated aiming at supporting blind persons in the task of identifying of landmarks. The first step was to investigate a way to avoid masking, a problem caused by technology that is characterized by a cognitive overload and the harmful interference of technology in the wearer’s capabilities of sensing the environment through their senses. In order to investigate masking, a Case Study was designed and carried out with a group of blind subjects. As a result, the wearable succeeded in avoiding masking. The approach used is considered useful as an alternative for researchers that investigate this problem in other contexts. Besides avoiding the masking, the proposed wearable enabled blind individuals explore more landmarks when compared to the approach of exploring with a white cane. Furthermore, this research also contributes with a set of recommendations for designers of wearables for blind mobility

Qualitative activity recognition of weight lifting exercises

Research on activity recognition has traditionally focused on discriminating between different activities, i.e. to predict which activity was performed at a specific point in time. The quality of executing an activity, the how (well), has only received little attention so far, even though it potentially provides useful information for a large variety of applications. In this work we define quality of execution and investigate three aspects that pertain to qualitative activity recognition: specifying correct execution, detecting execution mistakes, providing feedback on the to the user. We illustrate our approach on the example problem of qualitatively assessing and providing feedback on weight lifting exercises. In two user studies we try out a sensor- and a model-based approach to qualitative activity recognition. Our results underline the potential of model-based assessment and the positive impact of real-time user feedback on the quality of execution

Classificação periódica: um exemplo didático para ensinar análise de componentes principais Periodic classification: a didactic example to teach principal component analysis

<abstract language="eng">A dataset of chemical properties of the elements is used herein to introduce principal components analysis (PCA). The focus in this article is to verify the classification of the elements within the periodic table. The reclassification of the semimetals as metals or nonmetals emerges naturally from PCA and agrees with the current SBQ/IUPAC periodic table. Dataset construction, basic preprocessing, loading and score plots, and interpretation have been emphasized. This activity can be carried out even when students with distinct levels of formation are together in the same learning environment

A variable elimination method to improve the parsimony of MLR models using the successive projections algorithm

The successive projections algorithm (SPA) is a variable selection technique designed to minimize collinearity problems in multiple linear regression (MLR). This paper proposes a modification to the basic SPA formulation aimed at further improving the parsimony of the resulting MLR model. For this purpose, an elimination procedure is incorporated to the algorithm in order to remove variables that do not effectively contribute towards the prediction ability of the model as indicated by an F-test. The utility of the proposed modification is illustrated in a simulation study, as well as in two application examples involving the analysis of diesel and com samples by near-infrared (NIR) spectroscopy. The results demonstrate that the number of variables selected by SPA can be reduced without significantly compromising prediction performance. In addition, SPA is favourably compared with classic Stepwise Regression and full-spectrum PLS. A graphical user interface for SPA is available at www.ele.ita.br/similar to kawakami/spa/. (C) 2008 Elsevier B.V. All rights reserved