Analysing written production competence descriptors for academic and professional purposes and their calibration to the CEFR

The Common European Framework of Reference for Languages (CEFR) "describes in a comprehensive way what language learners have to learn to do in order to use a language for communication and what knowledge and skills they have to develop so as to be able to act effectively" (Council of Europe, 2001: 1). This paper reports on the findings of two studies whose purpose was to assess written production competence descriptors meant for their inclusion into the Academic and Professional English Language Portfolio KELP) for students of engineering and architecture. The main objective of these studies was to establish whether the language competence descriptors were a satisfactory valid tool in their language programmes from the point of view of clarity, relevance and reliability, as perceived by the students and fellow English for Academic Purposes (RAP) / English for Science and Technology (EST) instructors. The studies shed light on how to improve unsatisfactory descriptors. Results show that the final descriptor lists were on the whole well calibrated and fairly well written: the great majority was considered valid for both teachers and students involved.

Learning Analytics and Interactions in Virtual Learning Environments. A Comparative Study of Typologies and their Relationship with Academic Performance

Analysis of learning data (learning analytics) is a new research field with high growth potential. The main objective of Learning analytics is the analysis of data (interactions being the basic data unit) generated in virtual learning environments, in order to maximize the outcomes of the learning process; however, a consensus has not been reached yet on which interactions must be measured and what is their influence on learning outcomes. This research is grounded on the study of e-learning interaction typologies and their relationship with students? academic performance, by means of a comparative study between different interaction typologies (based on the agents involved, frequency of use and participation mode). The main conclusions are a) that classifications based on agents offer a better explanation of academic performance; and b) that each of the three typologies are able to explain academic performance in terms of some of their components (student-teacher and student-student interactions, evaluating students interactions and active interactions, respectively), with the other components being nonrelevant.

Survey on student motivation and approval of educational environment at Universidad Politécnica de Madrid within the European Higher Education area implementation

A recent study elaborated by Vicerrectorado de Ordenación Académica y Planificación Estratégica of Technical University of Madrid (UPM) defines the satisfaction of the university student body as "the response that the University offers to the expectations and demands of service of the students, considered in a general way ". Besides an indicator of academic and institutional insertion of the student, the assessment of student engagement allows us to adapt the academic offer and the extension services of the University to the real needs of the students. The process of convergence towards the European Higher Education Area (EHEA) raises the need to form in competitions, that is to say, of developing in our students capacities and knowledge beyond the purely theoretical-practical thing. Therefore, the perception and experience of the educational process and environment by the students is an important issue to be addressed to accomplish their expectations and achieve a curriculum accordingly to EHEA expectations. The present study aims to explore the student motivation and approval of the educational environment at the UPM. To this end a total of 97 students enrolled in the undergraduate program of Civil Engineering, Computer Engineering and Agronomic Engineering at UPM were surveyed. The survey consisted of 40 questions divided in three blocks. The first one of 20 questions of personal character in that they were gathering, besides the sex and the age, the degree of fulfilment, implication and dedication with the institution and the academic tasks. In the second block we identify 10 questions related to the perception of the student on the teaching quality, and finally a block of 10 questions regarding the Bologna Process. The students personal motivation was moderately high, with a score of 3.6 (all scores are provided on a 5-point scale), being the most valuable items obtaining a university degree (4,3) and the friendship between students (4,2). Any significant difference was shown between sexes (P=0.23) since the averages for this block of questions were of 3.7±0.3 and 3.5±0.4 for women and men respectively. The students are moderately satisfied with their graduate studies with an average score of 3,2, being the questions that reflect a minor satisfaction the research profile of the teachers (2,8) and the organization of the Schools (2,9). The best valued questions are related to the usefulness and quality of the degrees, with 3,5 and 3,4 respectively, and to the interest of the courses within the degree (3,4). For sexes, the results of this block of questions are similar (3.1±0.3 and 3.2±0.3 for men and women respectively=0.79). Also, there were no differences (P=0.39) between the students who arrange work and studies or do not work (3.1±0.2 and 3.2±0.3 respectively). In conclusion, students at UPM present an acceptable degree of motivation and satisfaction with regard to the studies and services that offer their respective Schools. Both characteristics receive the same value both for men and for women and so much for students who arrange work and studies as for those who devote themselves only to studying. In a significant way, students who are more engaged and are in-class attendants present the major degree of satisfaction.Overall, there is a great lack of information regarding the Bologna Process. In fact to the majority, they would like to know more on what it is, what it means and what changes will involve its implementation.

Predicting academic performance with learning analytics in virtual learning environments: A comparative study of three interaction classifications

Learning analytics is the analysis of static and dynamic data extracted from virtual learning environments, in order to understand and optimize the learning process. Generally, this dynamic data is generated by the interactions which take place in the virtual learning environment. At the present time, many implementations for grouping of data have been proposed, but there is no consensus yet on which interactions and groups must be measured and analyzed. There is also no agreement on what is the influence of these interactions, if any, on learning outcomes, academic performance or student success. This study presents three different extant interaction typologies in e-learning and analyzes the relation of their components with students? academic performance. The three different classifications are based on the agents involved in the learning process, the frequency of use and the participation mode, respectively. The main findings from the research are: a) that agent-based classifications offer a better explanation of student academic performance; b) that at least one component in each typology predicts academic performance; and c) that student-teacher and student-student, evaluating students, and active interactions, respectively, have a significant impact on academic performance, while the other interaction types are not significantly related to academic performance.

Physics and Mathematics in the Engineering Curriculum: Correlation with Applied Subjects

This paper presents a study in which the relationship between basic subjects (Mathematics and Physics) and applied engineering subjects (related to Machinery, Electrical Engineering, Topography and Buildings) in higher engineering education curricula is evaluated. The analysis has been conducted using the academic records of 206 students for five years. Furthermore, 34 surveys and personal interviews were conducted to analyze the connections between the contents taught in each subject and to identify student perceptions of the correlation with other subjects or disciplines. At the same time, the content of the different subjects have been analyzed to verify the relationship among the disciplines.Aproper coordination among subjects will allow students to relate and interconnect topics of different subjects, even with the ones learnt in previous courses, while also helping to reduce dropout rates and student failures in successfully accomplishing the different courses.