Increasing Staff and Student Capacity to Use the Communication Facility in Queen's Online in Order to Support Learning and Teaching on a BSW Programme

In this article the authors explore and evaluate developments in the use of information and communications technologies (ICT) within social work education at Queen's University Belfast since the inception of the new degree in social work. They look at the staff development strategy utilised to increase teacher confidence and competence in use of the Queen's Online virtual learning environment tools as well as the student experience of participation in modules involving online discussions. The authors conclude that the project provided further opportunity to reflect on how ICT can be used as a platform to support a whole course in a systematic and coordinated way and to ensure all staff remained abreast of ongoing developments in the use of ICT to support learning which is a normative expectation of students entering universities. A very satisfying outcome for the leaders is our observation of the emergence of other 'experts' in different aspects of use of ICT amongst the staff team. This project also shows that taking a team as opposed to an individual approach can be particularly beneficial

Conceptions of Quality and Approaches to Quality Assurance in Ontario’s Universities

Many international, political, and economic influences led to increased demands for development of new quality assurance systems for universities. Like many policies and processes that aim to assure quality, Ontario’s Quality Assurance Framework (QAF) did not define quality. This study sought to explore conceptions of quality and approaches to quality assurance used within Ontario’s universities. A document analysis of the QAF’s rationale and structure suggested that quality was conceived primarily as fitness for purpose, while suggested indicators represented an exceptional conception of quality. Ontario universities perpetuated such confusion by adopting the framework without customizing it to their institutional conceptions of quality. Drawing upon phenomenographic traditions, a qualitative investigation was conducted to better understand various conceptions of quality held by university administrators and to appreciate ways in which they implemented the QAF. Three main approaches to quality assurance were identified: (a) Defending Quality, characterized by conceptions of quality as exceptional, which focuses on administrative accountability and uses a hands-off strategy to defend traditional notions of quality inputs and resources; (b) Demonstrating Quality, characterized by conceptions of quality as fitness for purpose and value for money, which focuses on accountability to students and uses centralized engaged strategies to demonstrate how programs meet current priorities and intended outcomes; and (c) Enhancing Quality, characterized by conceptions of quality as transformation, which focuses on reflection and learning experience and uses engaged strategies to find new ways of improving learning and teaching. The development of a campus culture that values the institution’s function in student learning and quality teaching would benefit from Enhancing Quality approaches to quality assurance. This would require holistic consideration of the beliefs held by members of the institution, a clear articulation of the institution’s conceptions of quality, and a critical analysis of how these conceptions align with institutional practices and policies.

Evolution of Various Library Instruction Strategies: Using Student Feedback to Create and Enhance Online Active Learning Assignments

This case study traces the evolution of library assignments for biological science students from paper-based workbooks in a blended (hands-on) workshop to blended learning workshops using online assignments to online active learning modules which are stand-alone without any face-to-face instruction. As the assignments evolved to adapt to online learning supporting materials in the form of PDFs (portable document format), screen captures and screencasting were embedded into the questions as teaching moments to replace face-to-face instruction. Many aspects of the evolution of the assignment were based on student feedback from evaluations, input from senior lab demonstrators and teaching assistants, and statistical analysis of the students’ performance on the assignment. Advantages and disadvantages of paper-based and online assignments are discussed. An important factor for successful online learning may be the ability to get assistance.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

Cross-curricular approaches to teaching and learning.

Para profesores de primaria y todos aquellos involucrados en el diseño curricular. Aporta ideas prácticas sobre cómo el maestro puede utilizar la historia y la geografía como materias transversales para proporcionar un vehículo a través del cual los niños pueden aplicar los conocimientos y conceptos adquiridos en estas áreas. Además, los niños toman conciencia de cómo utilizar, desarrollar y ampliar los conocimientos que están adquiriendo de modo que el aprendizaje puede ser más integrado y relevante para ellos.

Inclusive approaches to teaching and learning mathematics

This chapter explores the role of mentors in supporting pre-service teachers to include all children in mathematics teaching, no matter what their individual needs.

Contemporary Approaches to Translation in the Classroom : A study of students' Attitudes and Strategies

The purpose of this study is to explore the strategies and attitudes of students towards translation in the context of language learning. The informants come from two different classes at an Upper Secondary vocational program. The study was born from the backdrop of discussions among some English teachers representing different theories on translation and language learning, meeting students endeavoring in language learning beyond the confinement of the classroom and personal experiences of translation in language learning. The curriculum and course plan for English at the vocational program emphasize two things of particular interest to our study; integration of the program outcomes and vocational language into the English course - so called meshed learning – and student awareness of their own learning processes. A background is presented of different contrasting methods in translation and language learning that is relevant to our discussion. However, focus is given to contemporary research on reforms within the Comparative Theory, as expressed in Translation in Language and Teaching (TILT), Contrastive Analysis and “The Third Space”. The results of the students’ reflections are presented as attempts to translate two different texts; one lyric and one technical vocational text. The results show a pragmatic attitude among the students toward tools like dictionaries or Google Translate, but also a critical awareness about their use and limits. They appear to prefer the use of first language to the target language when discussing the correct translation as they sought accuracy over meaning. Translation for them was a natural and problem-solving event worth a rightful place in language teaching.

Understanding the learning approaches of first-year accounting students

This study evolves from the broader educational research that indicates the characteristics of the student and the perceptions of the teaching/learning environment influence the quality of student learning. The model of learning developed in the paper is based on Biggs' (1987a) model of student learning together with the congruence model of vocational interests and work environments proposed by Holland (1985,1992). The model of learning was tested using a sample of 826 first year accounting students using structural equation modelling (SEM).

The findings provide substantive information about the learning approaches of students with vocational interests congruent with the task demands of a first year accounting course. Additionally, there is strong support for the association between student perceptions of the teaching/learning environment and approaches to learning. In particular the re specified model of student learning identifies the relationship between student perceptions of the appropriateness of workload and the adoption of a surface approach to learning.

Why models are advantageous to learning science

Models are used routinely in science classes to help explain scientific concepts; however, students are often unaware of the role, limitations and purpose of the particular model being used. This study investigated Grade 8-11 students’ views on models in science and used these results to propose a framework to show how models are involved in learning. The results show that students’ understanding of the role of models in learning science improved in later grades and that many students were able to distinguish the purpose of scientific models from teaching models. The results are used to identify the criteria students use to classify models and to support pedagogical approaches of using models in teaching science.