Perceptions of Doctoral Graduates on the Usefulness of Written Reflections as an Instructional Strategy

One of the goals of the Ed.D. in Leadership and Professional Practice at Trevecca Nazarene University is for candidates to be reflective practitioners. Since the inception of the program in 1999, written reflections as an instructional strategy has been encouraged by the administration and used by several professors. This focus is supported by the conceptual framework that informs all courses and programs in the School of Education and includes the national standards adopted by INTASC (Interstate New Teacher Assessment and Support Consortium) which calls for teacher education candidates to be reflective practitioners who plan, implement, and evaluate effectively. This standard is applied to all programs, including those at the master’s and doctoral levels. Research by Ballantyne and Packer (1995) in Studies in Continuing Education reported that the analysis of journal entries by 13 students enrolled in education doctoral programs confirmed the usefulness of journals in reflecting on and connecting academic learning and experience

Threshold Concepts Vs. Tricky Topics - Exploring the Causes of Student's Misunderstandings with the Problem Distiller Tool

This paper presents a study developed within the international project JuxtaLearn. This project aims to improve student understanding of threshold concepts by promoting student curiosity and creativity through video creation. The math concept of 'Division', widely referred in the literature as problematic for students, was recognised as a 'Tricky Topic' by teachers with the support of the Tricky Topic Tool and the Problem Distiller tool, two apps developed under the JuxtaLearn project. The methodology was based on qualitative data collected through Think Aloud protocol from a group of teachers of a public Elementary school as they used these tools. Results show that the Problem Distiller tool fostered the teachers to reflect more deeply on the causes of the students’ misunderstandings of that complex math concept. This process enabled them to develop appropriate strategies to help the students overcome these misunderstandings. The results also suggest that the stumbling blocks associated to the Tricky Topic ‘Division’ are similar to the difficulties reported in the literature describing Threshold Concepts. This conclusion is the key issue discussed in this paper and a contribution to the state of the art

A conceptual model for re ecting on expected learning vs. demonstrated student performance

© 2013, Australian Computer Society, Inc. Educators are faced with many challenging questions in designing an effective curriculum. What prerequisite knowledge do students have before commencing a new subject? At what level of mastery? What is the spread of capabilities between bare-passing students vs. the top-performing group? How does the intended learning specification compare to student performance at the end of a subject? In this paper we present a conceptual model that helps in answering some of these questions. It has the following main capabilities: capturing the learning specification in terms of syllabus topics and outcomes; capturing mastery levels to model progression; capturing the minimal vs. aspirational learning design; capturing confidence and reliability metrics for each of these mappings; and finally, comparing and re ecting on the learning specification against actual student performance. We present a web-based implementation of the model, and validate it by mapping the final exams from four programming subjects against the ACM/IEEE CS2013 topics and outcomes, using Bloom's Taxonomy as the mastery scale. We then import the itemised exam grades from 632 students across the four subjects and compare the demonstrated student performance against the expected learning for each of these. Key contributions of this work are the validated conceptual model for capturing and comparing expected learning vs. demonstrated performance, and a web-based implementation of this model, which is made freely available online as a community resource

Specifying computer-supported collaboration scripts

Collaboration scripts are activity programs which aim to foster collaborative learning by structuring interaction between learners. Computer-supported collaboration scripts generally suffer from the problem of being restrained to a specific learning platform and learning context. A standardization of collaboration scripts first requires a specification of collaboration scripts that integrates multiple perspectives from computer science, education and psychology. So far, only few and limited attempts at such specifications have been made. This paper aims to consolidate and expand these approaches in light of recent findings and to propose a generic framework for the specification of collaboration scripts. The framework enables a description of collaboration scripts using a small number of components (participants, activities, roles, resources and groups) and mechanisms (task distribution, group formation and sequencing)

The impact of a multi-strategy academic writing handbook on Emergent bilinguals’ cross-curricular writing competences

La escritura académica en una segunda lengua puede ser uno de los requerimientos más complejos en la educación superior debido a los elementos lingüísticos, estratégicos y procedimentales que esta abarca al igual que los procesos cognitivos superiores que involucra. A pesar de su presencia permanente en la academia, los profesores no han encontrado aún una forma apropiada para enseñar y evaluar la escritura que garantice el progreso de los estudiantes y el apoyo continuo a lo largo de su proceso de aprendizaje. De esta manera, este estudio de caso de métodos mixtos apunta a diseñar y evaluar la efectividad de un Manual de Referencia para la Escritura Académica (MREA) que pretende proveer la asistencia constante que los estudiantes necesitan para solidificar su conocimiento de escritura y el material pedagógico apropiado que los docentes requieren para unificar los prácticas de enseñanza y evaluación de la escritura; este manual está fundamentado en los enfoques de la escrita como proceso y basada en el género, análisis de errores y evaluación..

The role of pedagogical tools in active learning: a case for sense-making

Evidence from the research literature indicates that both audience response systems (ARS) and guided inquiry worksheets (GIW) can lead to greater student engagement, learning, and equity in the STEM classroom. We compare the use of these two tools in large enrollment STEM courses delivered in different contexts, one in biology and one in engineering. The instructors studied utilized each of the active learning tools differently. In the biology course, ARS questions were used mainly to check in with students and assess if they were correctly interpreting and understanding worksheet questions. The engineering course presented ARS questions that afforded students the opportunity to apply learned concepts to new scenarios towards improving students conceptual understanding. In the biology course, the GIWs were primarily used in stand-alone activities, and most of the information necessary for students to answer the questions was contained within the worksheet in a context that aligned with a disciplinary model. In the engineering course, the instructor intended for students to reference their lecture notes and rely on their conceptual knowledge of fundamental principles from the previous ARS class session in order to successfully answer the GIW questions. However, while their specific implementation structures and practices differed, both instructors used these tools to build towards the same basic disciplinary thinking and sense-making processes of conceptual reasoning, quantitative reasoning, and metacognitive thinking.Comment: 20 pages, 5 figure

Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings