E-Learning for Teachers and Trainers : Innovative Practices, Skills and Competences

Reproduction is authorised provided the source is acknowledged.Final Published versio

Technology Solutions for Developmental Math: An Overview of Current and Emerging Practices

Reviews current practices in and strategies for incorporating innovative technology into the teaching of remedial math at the college level. Outlines challenges, emerging trends, and ways to combine technology with new concepts of instructional strategy

Complete LibTech 2013 Print Program

PDF of the complete print program from the 2013 Library Technology Conferenc

Incorporating Online Instruction in Academic Libraries: Getting Ahead of the Curve

A sea change in higher education is shaping the way many libraries deliver instruction to their students and faculty. Years of technological innovation and changes in the way that people discover and use information has made online instruction an essential part of a library\u27s teaching and learning program. In order to evaluate our library\u27s online instruction program and to determine its future goals, we analyzed the technology, pedagogical models, organizational structures, administrative supports, and partnerships we would need in order to succeed. Our findings may be useful for libraries reassessing their own online instruction programs

Development of predicting model for safety behaviour based on safety psychology and working environment

The increasing trend of occupational accident due to unsafe act and unsafe condition especially in construction site suggests the need for more proactive safety assessment model. Therefore this research aimed to establish a prediction model of safety behaviour based on safety psychology and working environment factors in construction site. Theory of Planned Behaviour (TpB) was adapted to examine on the prediction model of safety behaviour among construction workers using safety psychology representing unsafe act and working environment factors representing unsafe condition. A modified perception questionnaire named Safety Psychometric Model (SPM) was proposed based on TpB questionnaire and safety attitude questionnaire (SQA). Previously, the approach has successfully applied in health care and manufacturing sector. The questionnaire has been validated by three industrial and academic experts. A total of 554 respondents among 92 construction site were selected as the subjects for analysis. Structural Equation Modelling (SEM) and Statistical Package for the Social Science (SPSS) was use for analysis purpose which involve correlation, regression and structural equation analysis. The results demonstrated that safety psychology and work environment factor was related positively with safety behaviour intention. The elements of workers’ attitude, subjective norm and perceived control that form the safety psychology context found to be significantly has the ability to predict safety behaviour. The demographics variances of personal and education background, working experiences and training background also determine as the factors of safety behaviour of the construction workers. The research also successfully established a safety behaviour prediction model that named Safety Psychometric Model. The model can be benefited by safety practitioners, organizations and researchers to explore the safety behaviour prediction. It also enhanced the knowledge in the area of employee behaviour prediction and modelling

Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning

The realities of the 21st-century learner require that schools and educators fundamentally change their practice. "Educators must produce college- and career-ready graduates that reflect the future these students will face. And, they must facilitate learning through means that align with the defining attributes of this generation of learners."Today, we know more than ever about how students learn, acknowledging that the process isn't the same for every student and doesn't remain the same for each individual, depending upon maturation and the content being learned. We know that students want to progress at a pace that allows them to master new concepts and skills, to access a variety of resources, to receive timely feedback on their progress, to demonstrate their knowledge in multiple ways and to get direction, support and feedback from—as well as collaborate with—experts, teachers, tutors and other students.The result is a growing demand for student-centered, transformative digital learning using competency education as an underpinning.iNACOL released this paper to illustrate the technical requirements and functionalities that learning management systems need to shift toward student-centered instructional models. This comprehensive framework will help districts and schools determine what systems to use and integrate as they being their journey toward student-centered learning, as well as how systems integration aligns with their organizational vision, educational goals and strategic plans.Educators can use this report to optimize student learning and promote innovation in their own student-centered learning environments. The report will help school leaders understand the complex technologies needed to optimize personalized learning and how to use data and analytics to improve practices, and can assist technology leaders in re-engineering systems to support the key nuances of student-centered learning

Improving School Improvement

PREFACEIn opening this volume, you might be thinking:Is another book on school improvement really needed?Clearly our answer is yes. Our analyses of prevailing school improvement legislation, planning, and literature indicates fundamental deficiencies, especially with respect to enhancing equity of opportunity and closing the achievement gap.Here is what our work uniquely brings to policy and planning tables:(1) An expanded framework for school improvement – We highlight that moving from a two- to a three-component policy and practice framework is essential for closing the opportunity and achievement gaps. (That is, expanding from focusing primarily on instruction and management/government concerns by establishing a third primary component to improve how schools address barriers to learning and teaching.)(2) An emphasis on integrating a deep understanding of motivation – We underscore that concerns about engagement, management of behavior, school climate, equity of opportunity, and student outcomes require an up-to-date grasp of motivation and especially intrinsic motivation.(3) Clarification of the nature and scope of personalized teaching – We define personalization as the process of matching learner motivation and capabilities and stress that it is the learner's perception that determines whether the match is a good one.(4) A reframing of remediation and special education – We formulate these processes as personalized special assistance that is applied in and out of classrooms and practiced in a sequential and hierarchical manner.(5) A prototype for transforming student and learning supports – We provide a framework for a unified, comprehensive, and equitable system designed to address barriers to learning and teaching and re-engage disconnected students and families.(6) A reworking of the leadership structure for whole school improvement --We outline how the operational infrastructure can and must be realigned in keeping with a three component school improvement framework.(7) A systemic approach to enhancing school-community collaboration – We delineate a leadership role for schools in outreaching to communities in order to work on shared concerns through a formal collaborative operational infrastructure that enables weaving together resources to advance the work.(8) An expanded framework for school accountability – We reframe school accountability to ensure a balanced approach that accounts for a shift to a three component school improvement policy.(9) Guidance for substantive, scalable, and sustainable systemic changes –We frame mechanisms and discuss lessons learned related to facilitating fundamental systemic changes and replicating and sustaining them across a district.The frameworks and practices presented are based on our many years of work in schools and from efforts to enhance school-community collaboration. We incorporate insights from various theories and the large body of relevant research and from lessons learned and shared by many school leaders and staff who strive everyday to do their best for children.Our emphasis on new directions in no way is meant to demean current efforts. We know that the demands placed on those working in schools go well beyond what anyone should be asked to do. Given the current working conditions in many schools, our intent is to help make the hard work generate better results. To this end, we highlight new directions and systemic pathways for improving school outcomes.Some of what we propose is difficult to accomplish. Hopefully, the fact that there are schools, districts, and state agencies already trailblazing the way will engender a sense of hope and encouragement to those committed to innovation.It will be obvious that our work owes much to many. We are especially grateful to those who are pioneering major systemic changes across the country. These leaders and so many in the field have generously offered their insights and wisdom. And, of course, we are indebted to hundreds of scholars whose research and writing is a shared treasure. As always, we take this opportunity to thank Perry Nelson and the host of graduate and undergraduate students at UCLA who contribute so much to our work each day, and to the many young people and their families who continue to teach us all.Respectfully submitted for your consideration,Howard Adelman & Linda Taylo

Teachers Know Best: Making Data Work For Teachers and Students

The Teachers Know Best research project seeks to encourage innovation in K - 12 education by helping product developers and those who procure resources for teachers better understand teachers' views. The intent of Making Data Work is to drill down to help educators, school leaders, and product developers better understand the challenges teachers face when working with this critical segment of digital instructional tools. More than 4,600 teachers from a nationally representative sample were surveyed about their use of data to drive instruction and the use of these tools.This study focuses on the potential of a specific subset of digital instructional tools: those that help teachers collect and make use of student data to tailor and improve instruction for individual students. The use of data is a crucial component in personalized learning, which ensures that student learning experiences -- what they learn and how, when, and where they learn it -- are tailored to their individual needs, skills, and interests and enable them to take ownership of their learning. Personalized learning is critical to meeting all students where they are, so they are neither bored with assignments that are too easy nor overwhelmed by work that is too hard