Purpose -The purpose of this paper is to examine existing learning innovation systems and propose a systematic methodology of delivering educational innovations in the right amount, in the right place and at the right time. Design/methodology/approach -Higher education is not effectively incorporating new discoveries in cognitive science and human learning into effective teaching strategies. In this paper, the authors explore the various impediments to change. To partially overcome these barriers, Drexel University, in collaboration with Untra Academic Management Solutions, LLC, has embarked on the development of a knowledge management system to assist instructors in obtaining, implementing, evaluating and disseminating new educational innovations. The system as envisioned would be capable of adapting to various educational environments and evolving with changes in curricula, faculty expectations, learning outcomes and student characteristics. Findings -The SocraticNet as a learning environment is stimulated, based on Socratic inquiry among teachers and learners. It is an interactive social network system utilising Web 2.0-based emerging technologies fostering communication and sharing among faculty, students and others (e.g. librarians) engaged in a particular course or other educational experience. Students learn by sharing what they know, by asking questions, judging and evaluating the retrieved information, and using this information efficiently in completing their assignments or research papers. This approach results in multidimensional information flow -instructor to instructor, instructor to student, student to instructor, student to student -which adds a new richness to the interactions between faculty and students providing the framework for a true learning community.Research limitations/implications -The present work has been conducted at one institution. This can be extended to include more institutions and tried with different disciplines. There are implications for changes in relation to teaching and learning approached adopted in higher education and also for development of technology tailored to address issues emanating from the scenario. Practical implications -The research work presented has the potential to stimulate debate to further develop and refine thinking on the role and use of technology directed at improving teaching and learning in higher education. Originality/value -This paper examines learning and teaching styles in higher education taking cognizance of conditions and factors impeding new innovations in practice. Details discussions are presented and unique suggestions are made.

Educational assessment using process management approaches is tacitly built upon business models which envision student learning outcomes as product specifications.These approaches often pay insufficient attention to student personality and lifestyle parameters and how these parameters interact with instructional approaches to affect student performance. To complicate matters, student attributes and their interactions with teaching approaches are not fixed and may change within the development of a single student and certainly do change from generation to generation. What is needed is a methodology that allows educators to assess important student parameters, monitor those parameters' interactions with teaching approaches and provide for timely intervention to ensure superior student learning achievement. The goal of the present work is to develop, test and implement a scalable and transferrable information technology-assisted knowledge management system that monitors important student characteristics and analyzes the impact of those factors on learning in time for effective intervention. I. PROJECT OVERVIEW AND FEASIBILITYThe main thrust of our efforts is to increase program success in attaining student learning outcomes and engineering program objectives by correlating selected characteristics of students, instructors, courses and curricula with student academic performance. To accomplish this, we will design, implement and test a knowledge management (KM) system that obtains high quality, high resolution, statistically significant information to facilitate decisions concerning the most critical factors in student learning and how and when they can be most impacted by intervention and instructional innovation. The kind of intervention and/or innovation can then be approached with a high degree of confidence and reliability. Three types of studies are currently underway in our School.1) Correlational Studies investigating the impact of student, instructor and course/curricular attributes and characteristics on student learning outcomes and program objectives; 2) Chronobiological Studies examining the effects of sleep and scheduling on student performance and 3) Instructional Methods Studies employing anExperimental Instructional Laboratory to demonstrate how educational interventions may be accurately assessed.Each of these studies depends on an integrated KM system to collect and evaluate relevant data.The design and implementation of an on-going, semiautomatic system using information technology and statistical analysis which can be integrated with Accreditation Board for Engineering and Technology (ABET)-mandated assessment and evaluation procedures will allow an academic unit to conduct regular and timely surveillance, assessment and improvement of any engineering education program in any college or university. Too often, innovative designs for educational enhancement fall into disrepair because those designs embody the unintended consequences of built-in obsolescence. Many designs have failed due to their s...

A major difficulty in assessment is the problem known as 'closing the loop' -ensuring that assessment data is used effectively for program improvement and to enhance student learning. There are a number of reasons why current assessment procedures do not always succeed at this necessary phase of the process. First and foremost is that assessment has been tied to accreditation and viewed by many faculty and administrators as a necessary evil to be dealt with as little expenditure of time and effort as possible. As long as some program changes can be linked to the assessment process -thus satisfying the external accreditors-the bulk of the data being collected can be safely ignored. A second factor is the data itself. In order for the assessment process to be effective, the right kind of data must be collected in the right amount. However, there seems little consensus as to the kind and amount of data to collect. Finally, the nature of faculty instruction in higher education can itself be an impediment. Faculty instructors are often unaware of how their particular courses fit into the overall curriculum, beyond vague knowledge of what pre-requisite courses should have been taught.

An evidence-based intervention system is proposed to provide for guided evolution of engineering education programs. Too often, innovative designs for educational enhancement fall into disrepair because they embodied the unintended consequence of built-in obsolescence. The ineffectiveness of many designs has been resident in a static view of learning and teaching styles, personnel-dependence, an inability to manage changes in program size, and/or a lack of portability and adoption by the larger educational community. To avoid these specific pitfalls in our design for educational enhancement, we are: (1) employing a dynamic view of learning and teaching styles where the characteristics of student and faculty are periodically measured to establish an assessment process calibration, (2) using knowledge management systems to process voluminous data collection and analysis in an efficient and flexible manner, (3) using a modular design of an established assessment paradigm that provides points of real-time intervention to responsively optimize educational practices, and (4) using a widely-practiced assessment paradigm that confers transferability of the process with its value-added, best-practices modifications to other educational systems. The approach to accomplish these goals is based upon decision support software currently in use in business and health care. The implementation of Instructional Decision Support System (IDSS) approaches will provide rapid feedback of assessment data combined with student characteristics to empower faculty instructors and enhance student learning.Preliminary data has provided a basic proof-of-concept for the IDSS approach. Data from the Index of Learning Styles indicated that the students surveyed were sequential, as opposed to global, learners. Instructors found that redesigning some courses to provide a more sequential, step-by-step style enhanced the student experience in selected courses. Other data showed that students surveyed were not as positively inclined towards engineering as might be expected for a biomedical engineering program. If confirmed, this data can be used to provide support for developing new educational experiences targeted to improve students' attitudes towards the discipline.

Revisions in the criteria for accreditation of engineering programs by the Accreditation Board for Engineering and Technology (ABET), especially with regard to Criterion 3: Program Outcomes and Assessment, have the potential to significantly enhance engineering education. Several factors may inhibit these revisions from reaching this potential. Among these are the tendency of faculty to view assessment as means to the end of obtaining ABET accreditation and the recent tendency to view students as customers within a continuous quality improvement (CQI) paradigm. While neither viewpoint is entirely incorrect, when these perspectives dominate curriculum review, many of the advantages of true curricular assessment and quality improvement are lost. We believe it to be more advantageous to regard students as products within an engineering design and manufacturing paradigm when developing assessment and improvement processes for curricula. In this paper, we will show how we have used the engineering design paradigm, coupled with ABET requirements, to develop an assessment and feedback approach that maps performance criteria in such a manner as to allow timely intervention at an individual student as well as programmatic level. We will demonstrate how to decompose student learning outcomes into performance criteria at a resolution geared for intervention rather than just assessment. Finally, we will describe a Web-based knowledge management system called AEFIS (Academic Evaluation, Feedback and Intervention System) which manages the data in such a way as to maximize the ability to provide continuous quality improvement while minimizing additional faculty labor.