Cindy Ives

Bio: Cindy Ives is an academic researcher from Athabasca University. The author has contributed to research in topics: Learning Management & Technology integration. The author has an hindex of 9, co-authored 19 publications receiving 491 citations.

Measuring Use and Creation of Open Educational Resources in Higher Education.

Abstract: The open educational resources initiative has been underway for over a decade now and higher education institutions are slowly adopting open educational resources (OER). The use and creation of OER are important aspects of adoption and both are needed for the benefits of OER to be fully realized. Based on the results of a survey developed to measure the readiness of faculty and staff to adopt OER, this paper focuses on the measurement of OER use and creation, and identifies factors to increase both. The survey was administered in September 2012 to faculty and staff of Athabasca University, Canada’s open university. The results offer a snapshot of OER use and creation at one university. The survey tool could provide a mechanism to compare and contrast OER adoption with other higher education institutions. Forty-three percent of those in the sample are using OER and 31% are creating OER. This ratio of use to creation is introduced as a possible metric to measure adoption.

AAT: a tool for accessing and analysing students' behaviour data in learning systems

Abstract: In online learning environments, teachers and course designers often get little feedback about how students actually interact with and learn in online courses. Most of the learning systems used by educational institutions store comprehensive log data associated with students' behaviours and actions. However, these systems typically reveal or report on very general and limited information based on this data. In order to provide teachers and course designers with more detailed and meaningful information about students' behaviour and their use of learning resources within online courses, an analytics tool has been developed. The tool incorporates functionality to access and analyse data related to students' behaviours in learning systems. This tool can provide valuable information about students' learning processes allowing the identification of difficult or inappropriate learning material, and can therefore significantly contribute to the design of improved student support activities and resources.

A Flexible Mechanism for Providing Adaptivity Based on Learning Styles in Learning Management Systems

Abstract: While today’s learning management systems (LMSs) provide lot of support for teachers to assist them in holding online courses, they typically do not consider students’ individual differences in the composition and structure of courses In this paper, we introduce a mechanism for extending LMSs’ functionality to provide learners with courses that fit their individual learning styles, using adaptive sorting and adaptive annotation in order to highlight the learning objects (LOs) that support students’ learning process the best The mechanism enables teachers to add adaptivity to their already existing courses, using a flexible course structure in order to avoid limiting the richness of the learning resources and materials Besides being flexible to teachers’ needs, the adaptive mechanism aims at asking teachers for as little as possible additional effort when using it, requiring teachers only to choose the corresponding type of LO when creating an LO in the authoring tool of the LMS

Planning for Integrating Teaching Technologies.

Abstract: Teaching technologies offer pedagogical advantages which vary with specific contexts. Successfully integrating them hinges on clearly identifying pedagogical goals, then planning for the many decisions that technological change demands. In examining different ways of organizing this process, we have applied planning tools from other domains - Fault Tree Analysis and Capability Maturity Modeling- at the school and college levels. In another approach, we have examined attempts to broadly model the integration process at the university level. Our studies demonstrate that the use of a variety of tools and techniques can render the integration of teaching technologies more systematic.

Data mining in education

Abstract: Applying data mining DM in education is an emerging interdisciplinary research field also known as educational data mining EDM. It is concerned with developing methods for exploring the unique types of data that come from educational environments. Its goal is to better understand how students learn and identify the settings in which they learn to improve educational outcomes and to gain insights into and explain educational phenomena. Educational information systems can store a huge amount of potential data from multiple sources coming in different formats and at different granularity levels. Each particular educational problem has a specific objective with special characteristics that require a different treatment of the mining problem. The issues mean that traditional DM techniques cannot be applied directly to these types of data and problems. As a consequence, the knowledge discovery process has to be adapted and some specific DM techniques are needed. This paper introduces and reviews key milestones and the current state of affairs in the field of EDM, together with specific applications, tools, and future insights. © 2012 Wiley Periodicals, Inc.

Seven Principles for Good Practice in Undergraduate Education: Faculty Inventory. Institutional Inventory.

Abstract: Arthur Chickering is Distinguished Professor of Higher Education at Memphis State University. On leave from the Directorship of the Center for the Study of Higher Education at Memphis State, he is Visiting Professor at George Mason University. Zelda Gamson is a sociologist who holds appointments at the John W. McCormack Institute of Public Affairs at the University of Massachusetts-Boston and in the Center for the Study of Higher and Postsecondary Education at the University of Michigan.

Definition, framework and research issues of smart learning environments - a context-aware ubiquitous learning perspective

Abstract: The rapid progress of mobile, wireless communication and sensing technologies has enabled the development of context-aware ubiquitous learning (u-learning) environments, which are able to detect the real-world learning status of students as well as the environmental contexts. Accordingly, appropriate information can be provided to individual students in the right place and at the right time. However, researchers have indicated that, to support students to learn in real-world contexts in smart ways, more factors need to be taken into account when designing and developing learning systems. In this paper, the definition and criteria of smart learning environments are presented from the perspective of context-aware ubiquitous learning. A framework is also presented to address the design and development considerations of smart learning environments to support both online and real-world learning activities. Moreover, some emerging technologies that might facilitate the development of smart learning environments as well as the features and criteria of smart learning are addressed. Finally, research issues related to smart learning are provided.

Design and Implementation of a Learning Analytics Toolkit for Teachers

Abstract: Introduction Learning Management Systems (LMS) or Virtual Learning Environments (VLE) are widely used and have become part of the common toolkits of educators (Schroeder, 2009). One of the main goals of the integration of traditional teaching methods with technology enhancements is the improvement of teaching and learning quality in large university courses with many students. But does utilizing a VLE automatically improve teaching and learning? In our experience, many teachers just upload existing files, like lecture slides, handouts and exercises, when starting to use a VLE. Thereby availability of learning resources is improved. For improving teaching and learning it could be helpful to create more motivating, challenging, and engaging learning materials and e.g., collaborative scenarios to improve learning among large groups of students. Teachers could e.g., use audio and video recordings of their lectures or provide interactive, demonstrative multimedia examples and quizzes. If they put effort in the design of such online learning activities, they need tools that help them observe the consequences of their actions and evaluate their teaching interventions. They need to have appropriate access to data to assess changing behaviors and performances of their students to estimate the level of improvement that has been achieved in the learning environment. With the establishment of TEL, a new research field, called Learning Analytics, is emerging (Elias, 2011). This research field borrows and synthesizes techniques from different related fields, such as Educational Data Mining (EDM), Academic Analytics, Social Network Analysis or Business Intelligence (BI), to harness them for converting educational data into useful information and thereon to motivate actions, like self-reflecting ones previous teaching or learning activities, to foster improved teaching and learning. The main goal of BI is to turn enterprise data into useful information for management decision support. However, Learning Analytics, Academic Analytics, as well as EDM more specifically focus on tools and methods for exploring data coming from educational contexts. While Academic Analytics take a university-wide perspective, including also e.g., organizational and financial issues (Campbell & Oblinger, 2007), Learning Analytics as well as EDM focus specifically on data about teaching and learning. Siemens (2010) defines Learning Analytics as "the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning." It can support teachers and students to take action based on the evaluation of educational data. However, the technology to deliver this potential is still very young and research on understanding the pedagogical usefulness of Learning Analytics is still in its infancy (Johnson et al., 2011b; Johnson et al., 2012). It is a current goal at RWTH Aachen University to enhance its VLE--the learning and teaching portal L2P (Gebhardt et al., 2007)--with user-friendly tools for Learning Analytics, in order to equip their teachers and tutors with means to evaluate the effectiveness of TEL within their instructional design and courses offered. These teachers still face difficulties, deterring them from integrating cyclical reflective research activities, comparable to Action Research, into everyday practice. Action Research is characterized by a continuing effort to closely interlink, relate and confront action and reflection, to reflect upon one's conscious and unconscious doings in order to develop one's actions, and to act reflectively in order to develop one's knowledge." (Altrichter et al., 2005, p. 6). A pre-eminent barrier is the additional workload, originating from tasks of collecting, integrating, and analyzing raw data from log files of their VLE (Altenbernd-Giani et al., 2009). To tackle these issues, we have developed the "exploratory Learning Analytics Toolkit" (eLAT). …

Are We Asking the Right Questions?: A Conceptual Review of the Educational Development Literature in Higher Education

Abstract: This is a conceptual review of the literature variously referred to as faculty development, educational development, instructional development, and academic development in higher education. Previous empirical reviews covering more than 30 years of published literature could draw only tentative and weak conclusions about the effectiveness of educational development practices. The authors used different questions that queried the nature of educational development practice and the thinking underlying practice. Their conceptual review yielded a framework with six foci of practice (skill, method, reflection, disciplinary, institutional, and action research or inquiry) that was drawn from an analysis of the design elements of the educational development practices in the research they reviewed and from an analysis of the conceptual, theoretical, and empirical literature cited by those articles. This six-cluster framework provides a new way of thinking about the design of practice and a more meaningful basis for ...