Self-regulated learning in higher education : strategies adopted by computer programming students

Trabalho apresentado em PAEE/ALE’2016, 8th International Symposium on Project Approaches in Engineering Education (PAEE) and 14th Active Learning in Engineering Education Workshop (ALE)

Collaborative Networked Organizations as System of Systems: A Model-Based Engineering Approach

Part 6: Engineering and Implementation of Collaborative Networks

A text analytics evaluation of a first-year engineering project-based unit

In the undergraduate engineering program at Griffith University in Australia, the unit 1006ENG Design and Professional Skills aims to provide an introduction to engineering design and professional practice through a project-based learning (PBL) approach to problem solving. It provides students with an experience of PBL in the first-year of their programme. The unit comprises an underpinning lecture series, design work including group project activities, an individual computer-aided drawing exercise/s and an oral presentation. Griffith University employs a ‘Student Experience of Course’ (SEC) online survey as part of its student evaluation of teaching, quality improvement and staff performance management processes. As well as numerical response scale items, it includes the following two questions inviting open-ended text responses from students: i) What did you find particularly good about this course? and ii) How could this course be improved? The collection of textual data in in student surveys is commonplace, due to the rich descriptions of respondent experiences they can provide at relatively low cost. However, historically these data have been underutilised because they are time consuming to analyse manually, and there has been a lack of automated tools to exploit such data efficiently. Text analytics approaches offer analysis methods that result in visual representations of comment data that highlight key individual themes in these data and the relationships between those themes. We present a text analytics-based evaluation of the SEC open-ended comments received in the first two years of offer of the PBL unit 1006ENG. We discuss the results obtained in detail. The method developed and documented here is a practical and useful approach to analysing/visualising open-ended comment data that could be applied by others with similar comment data sets.

MINING AND VERIFICATION OF TEMPORAL EVENTS WITH APPLICATIONS IN COMPUTER MICRO-ARCHITECTURE RESEARCH

Computer simulation programs are essential tools for scientists and engineers to understand a particular system of interest. As expected, the complexity of the software increases with the depth of the model used. In addition to the exigent demands of software engineering, verification of simulation programs is especially challenging because the models represented are complex and ridden with unknowns that will be discovered by developers in an iterative process. To manage such complexity, advanced verification techniques for continually matching the intended model to the implemented model are necessary. Therefore, the main goal of this research work is to design a useful verification and validation framework that is able to identify model representation errors and is applicable to generic simulators. The framework that was developed and implemented consists of two parts. The first part is First-Order Logic Constraint Specification Language (FOLCSL) that enables users to specify the invariants of a model under consideration. From the first-order logic specification, the FOLCSL translator automatically synthesizes a verification program that reads the event trace generated by a simulator and signals whether all invariants are respected. The second part consists of mining the temporal flow of events using a newly developed representation called State Flow Temporal Analysis Graph (SFTAG). While the first part seeks an assurance of implementation correctness by checking that the model invariants hold, the second part derives an extended model of the implementation and hence enables a deeper understanding of what was implemented. The main application studied in this work is the validation of the timing behavior of micro-architecture simulators. The study includes SFTAGs generated for a wide set of benchmark programs and their analysis using several artificial intelligence algorithms. This work improves the computer architecture research and verification processes as shown by the case studies and experiments that have been conducted.

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction:a review

Support Vector Machines (SVMs) are widely used classifiers for detecting physiological patterns in Human-Computer Interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the application of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables, and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

Using Research Methods in Human Computer Interaction to Design Technology for Resilience

Research in human computer interaction (HCI) covers both technological and human behavioural concerns. As a consequence, the contributions made in HCI research tend to be aware to either engineering or the social sciences. In HCI the purpose of practical research contributions is to reveal unknown insights about human behaviour and its relationship to technology. Practical research methods normally used in HCI include formal experiments, field experiments, field studies, interviews, focus groups, surveys, usability tests, case studies, diary studies, ethnography, contextual inquiry, experience sampling, and automated data collection. In this paper, we report on our experience using the evaluation methods focus groups, surveys and interviews and how we adopted these methods to develop artefacts: either interface’s design or information and technological systems. Four projects are examples of the different methods application to gather information about user’s wants, habits, practices, concerns and preferences. The goal was to build an understanding of the attitudes and satisfaction of the people who might interact with a technological artefact or information system. Conversely, we intended to design for information systems and technological applications, to promote resilience in organisations (a set of routines that allow to recover from obstacles) and user’s experiences. Organisations can here also be viewed within a system approach, which means that the system perturbations even failures could be characterized and improved. The term resilience has been applied to everything from the real estate, to the economy, sports, events, business, psychology, and more. In this study, we highlight that resilience is also made up of a number of different skills and abilities (self-awareness, creating meaning from other experiences, self-efficacy, optimism, and building strong relationships) that are a few foundational ingredients, which people should use along with the process of enhancing an organisation’s resilience. Resilience enhances knowledge of resources available to people confronting existing problems.

Computer-based monitoring platform for renewable energy systems: Four experimental application cases using NI LabVIEW

Sustainability and responsible environmental behaviour constitute a vital premise in the development of the humankind. In fact, during last decades, the global energetic scenario is evolving towards a scheme with increasing relevance of Renewable Energy Sources (RES) like photovoltaic, wind, biomass and hydrogen. Furthermore, hydrogen is an energy carrier which constitutes a mean for long-term energy storage. The integration of hydrogen with local RES contributes to distributed power generation and early introduction of hydrogen economy. Intermittent nature of many of RES, for instance solar and wind sources, impose the development of a management and control strategy to overcome this drawback. This strategy is responsible of providing a reliable, stable and efficient operation of the system. To implement such strategy, a monitoring system is required.The present paper aims to contribute to experimentally validate LabVIEW as valuable tool to develop monitoring platforms in the field of RES-based facilities. To this aim, a set of real systems successfully monitored is exposed.