Scaffolding students' learning in EME150 introduction to learners and learning theory : on looking back

This is a reflective article on the importance scaffolding in the EME 150 unit taught in collaboration with Deakin University Australia. Being the first unit introduced in the second semester of the first academic year, students were given a lot of support to enhance their understanding and learning since this curriculum was solely developed by Deakin University and introduced for the first time in teachers education curriculum. The scaffolding tools discussed in this article enabled students to a) establish deep learning of the theory. b) engage in collaborative and engaged learning which established good ethical relations between students c) transfer learning by applying theory into practice.

An interview schedule for use in the assessment of tertiary students' learning development needs

The initial interview is an important aspect of development of and intervention in tertiary student learning. Yet there are no published interview schedules available to psychologists working in the area of tertiary academic skills development. This paper presents an interview schedule for use with individual tertiary students seeking assistance with learning and academic skills development. Some preliminary comments about the application of the schedule are also offered.

Machine learning approaches for modeling spammer behavior

Spam is commonly known as unsolicited or unwanted email messages in the Internet causing potential threat to Internet Security. Users spend a valuable amount of time deleting spam emails. More importantly, ever increasing spam emails occupy server storage space and consume network bandwidth. Keyword-based spam email filtering strategies will eventually be less successful to model spammer behavior as the spammer constantly changes their tricks to circumvent these filters. The evasive tactics that the spammer uses are patterns and these patterns can be modeled to combat spam. This paper investigates the possibilities of modeling spammer behavioral patterns by well-known classification algorithms such as Naïve Bayesian classifier (Naive Bayes), Decision Tree Induction (DTI) and Support Vector Machines (SVMs). Preliminary experimental results demonstrate a promising detection rate of around 92%, which is considerably an enhancement of performance compared to similar spammer behavior modeling research.

Resuscitating students’ learning : exploring the “Living Dead” phenomenon

There is research spanning the 20th century on student disengagement. Despite all the research, the problem remains. It is time to adopt a different perspective. This article attempts to make transparent the influences on disengagement in schools by applying Jean Gebser’s (1985) empirical phenomenological study of cultural consciousness. What differentiates this approach from previous arguments is the basic premise that the “problem” of disengagement lies not with an individual or group, but with the cultural consciousness.

The design of a syllabus for translation students: learning outcomes in the subjects of spanish language

[EN]In the new design of educational programs in European Higher Education Area (EHEA), what defines a subject it is Learning Outcomes (LO). These LO, as explicit and precise declarations, turn into the center of teaching and learning process. Keeping this change is mind, our research examines the Educational Guides (EG) of Spanish Language (SL) through a list of verbs, according to the graduation of educacionational objectives of Bllom's Taxonomy (2014-2015)

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Traditional education vs modern education. What is the impact of teaching techniques' evolution on students learning process?

The main objective of this article is to focus on the analysis of teaching techniques, ranging from the use of the blackboard and chalk in old traditional classes, using slides and overhead projectors in the eighties and use of presentation software in the nineties, to the video, electronic board and network resources nowadays. Furthermore, all the aforementioned, is viewed under the different mentalities in which the teacher conditions the student using the new teaching technique, improving soft skills but maybe leading either to encouragement or disinterest, and including the lack of educational knowledge consolidation at scientific, technology and specific levels. In the same way, we study the process of adaptation required for teachers, the differences in the processes of information transfer and education towards the student, and even the existence of teachers who are not any longer appealed by their work due which has become much simpler due to new technologies and the greater ease in the development of classes due to the criteria described on the new Grade Programs adopted by the European Higher Education Area. Moreover, it is also intended to understand the evolution of students’ profiles, from the eighties to present time, in order to understand certain attitudes, behaviours, accomplishments and acknowledgements acquired over the semesters within the degree Programs. As an Educational Innovation Group, another key question also arises. What will be the learning techniques in the future?. How these evolving matters will affect both positively and negatively on the mentality, attitude, behaviour, learning, achievement of goals and satisfaction levels of all elements involved in universities’ education? Clearly, this evolution from chalk to the electronic board, the three-dimensional view of our works and their sequence, greatly facilitates the understanding and adaptation later on to the business world, but does not answer to the unknowns regarding the knowledge and the full development of achievement’s indicators in basic skills of a degree. This is the underlying question which steers the roots of the presented research.

Scaffolding and bilingual shared reading experiences: Promoting primary school students' learning and development

This paper explores the connections between scaffolding, second language learning and bilingual shared reading experiences. A socio- cultural theory of cognition underpins the investigation, which involved implementing a language and culture awareness program (LCAP) in a year 4 classroom and in the school community. Selected passages from observations are used to analyse the learning of three students, particularly in relation to languages other than English (LOTE). As these three case study students interacted in the classroom, at home and in the community, they co-constructed, appropriated and applied knowledge form one language to another. Through scaffolding, social spaces were constructed, where students learning and development were extended through a variety of activities that involved active participation, such as experimenting with language, asking questions and making suggestions. Extending these opportunities for student learning and development is considered in relation to creating teaching and learning environments that celebrate socio-cultural and linguistic diversity.