Quality Indicators of Online Programs

The continued growth of online programs in higher education has resulted in concerns about how institutions monitor the quality of their online programs. These concerns indicate a need for a process by which online programs may be evaluated and compared. They provided the impetus for this study, the goals of which were to identify quality indicators specific to community college online programs and to determine stakeholders' perceived importance of those indicators.

Categories of indicators were identified through a literature review, and these items were used to guide the development of a Delphi study to identify potential indicators. The results of the Delphi study were then used to create a three-part Stakeholder Survey designed to collect input on perceived levels of importance for each potential indicator using the magnitude estimation technique. The Stakeholder Survey was also used to validate the results of the Delphi. To refine the results of the Delphi study and Stakeholder Survey, a final survey was distributed to a group of distance learning experts, identified through their scholarly research and professional activity. The participants were asked to review the earlier results and classify each item as a factor, indicator, or other according to definitions provided.

The three research stages produced a set of potential data sources that a community college may want to pursue when assessing the effectiveness of its online programs and services. Each of the potential sources of data will be reviewed with a goal towards identifying specific indicators that may be used in developing future instruments.     

PPBS in higher education planning and management: Part I,an overview

Higher education in the United States and elsewhere is beset by crises: crises of public confidence, questions of continuing relevance, doubts about continuing the emphasis on doctoral instruction, and a very real financial crisis. In response, governing boards and governmental agencies are devoting increasing attention to the management of higher education. Part of this response has been a heightened interest in formal planning-programming-budgeting-systems (PPBS); in fact, several states have legislated the adoption of PPBS for higher educational planning and decision making. Similar interest has been evidenced in other countries. Therefore, it is an appropriate time to reconsider the nature and role of PPBS and its potential impact on higher education. This paper describes the salient characteristics of PPBS and traces the development of PPBS and related analytical techniques in governmental agencies and institutions of higher education. A second paper will illustrate both the concepts and the implementation of PPBS by a detailed exposition of the University of California's experience with PPBS. Finally, in a third paper we suggest an alternative view of policy analysis for educational planning which is a departure from traditional PPBS. We conclude with general observations and specific recommendations to educational managers seeking to improve their resource allocation procedures.     

Self-modeling as an intervention to increase student classroom participation

The effect of self-modeling as an intervention to increase individual participatory behavior in the classroom was investigated using a multiple baseline design across three second grade students with a follow-up. In addition, a control student was employed to further investigate the effects of the intervention. Self-modeling is defined as the positive change in behavior resulting from spaced viewing of oneself on edited tapes depicting exemplary behavior. Students viewed edited videotapes of themselves successfully volunteering to participate in class by raising their hand. The three students, during baseline, had a mean participation rate ranging between 8% and 24% compared with the control student's rate ranging between 53% and 63%. During intervention, the mean participation rate ranged between 28% and 60% compared with the control student's rate ranging between 43% and 46%. At follow-up, students had a mean percentage rate ranging between 44% and 64% compared with the control student's rate of 53%. Thus, they more closely approximated or surpassed the control student's mean rate of participation during intervention and follow-up, suggesting that the self-modeling intervention was effective in increasing individual participatory behavior in the classroom. © 1998 John Wiley & Sons, Inc.     

Can Examinees Use a Review Option to Obtain Positively Biased Ability Estimates on a Computerized Adaptive Test?

Part of the controversy about allowing examinees to review and change answers to previous items on computerized adaptive tests (CATs) centers on a strategy for obtaining positively biased ability estimates attributed to Wainer (1993) in which examinees intentionally answer items incorrectly before review and to the best of their abilities upon review. Our results, based on both simulated and live testing data, showed that there were instances in which the Wainer strategy yielded inflated ability estimates as well as instances in which it yielded deflated ability estimates. The success of the strategy in inflating ability estimates depended on the ability estimation method used (maximum likelihood versus Bayesian), the examinee's true ability level, the standard error of the ability estimate, the examinee's ability to implement the strategy, and the type of decision made from the ability estimate. We discuss approaches to dealing with the Wainer strategy in operational CAT settings.     

Effects of contextual cues previously paired with footshock or illness on behavior and pain sensitivity in the rat

Rats were used in four experiments to study the effects on behavior and pain sensitivity of exposure to a context previously paired with footshock or injection of the emetic drug lithium chloride (LiCl). Exposure to a context previously paired with footshock or injection of LiCl provoked the species-typical defense response of freezing (Experiments 1A and 1B). Exposure to a context previously paired with footshock additionally produced hypoalgesia when rats were tested using the tailflick test (Experiment 1A). By contrast, exposure to a context previously paired with injection of LiCl produced hyperalgesia when rats were tested using the tailflick test (Experiment 1B). However, exposure to a context previously paired with injection of LiCl did provoke hypoalgesia when rats were tested for pain sensitivity using either the hotplate or formalin tests (Experiment 2), which was mediated by the release of endogenous opioid peptides (Experiment 3). These results are discussed with reference to the processes governing associative regulation of defensive behavior and pain control.     

Teaching Lean Six Sigma within A Supply Chain Context: The Airplane Supply Chain Simulation

Lean six sigma is a management methodology that firms can employ to achieve substantial improvement in supply chain performance. However, few pedagogical exercises facilitate students’ use of a comprehensive set of lean six sigma principles within a supply chain context. We describe the Airplane Supply Chain Simulation that helps students understand how lean six sigma concepts may be leveraged to improve supply chain performance. The basis of this simulation is a four‐tier supply chain, consisting of suppliers (two tiers), a manufacturer, and a customer, that produces three models of paper airplanes to meet randomly distributed customer demand. In the first of three successive runs, a highly structured simulation is executed in which supply chain roles are well defined, material flows are convoluted, and a “push” production strategy is followed. The first simulation as the “current state” and, for the second and third simulation runs, challenge competing student teams to leverage lean six sigma concepts to develop a “future state” that enables the fulfillment of all customer orders at the lowest cost. Results based on statistical analyses of survey response data from 194 MBA students show that the Airplane Supply Chain Simulation is an effective participative, team‐based learning tool.     

Sorting of circulating tumor cells (MV3-melanoma) and red blood cells using non-inertial lift

We demonstrate the method of non-inertial lift induced cell sorting (NILICS), a continuous, passive, and label-free cell sorting approach in a simple single layer microfluidic device at low Reynolds number flow conditions. In the experiments, we exploit the non-inertial lift effect to sort circulating MV3-melanoma cells from red blood cell suspensions at different hematocrits as high as 9%. We analyze the separation process and the influence of hematocrit and volume flow rates. We achieve sorting efficiencies for MV3-cells up to E_MV3 = 100% at Hct = 9% and demonstrate cell viability by recultivation of the sorted cells.     

Robust observer-based fault estimation and accommodation of discrete-time piecewise linear systems

In this paper a new integrated observer-based fault estimation and accommodation strategy for discrete-time piecewise linear (PWL) systems subject to actuator faults is proposed. A robust estimator is designed to simultaneously estimate the state of the system and the actuator fault. Then, the estimate of fault is used to compensate for the effect of the fault. By using the estimate of fault and the states, a fault tolerant controller using a PWL state feedback is designed. The observer-based fault-tolerant controller is obtained by the interconnection of the estimator and the state feedback controller. We show that separate design of the state feedback and the estimator results in the stability of the overall closed-loop system. In addition, the input-to-state stability (ISS) gain for the closed-loop system is obtained and a procedure for minimizing it is given. All of the design conditions are formulated in terms of linear matrix inequalities (LMI) which can be solved efficiently. Also, performance of the estimator and the state feedback controller are minimized by solving convex optimization problems. The efficiency of the method is demonstrated by means of a numerical example.     

Evaluating R&D investment efficiency in China's high-tech industry

Research and development (R&D) investment activity plays a crucial role in developing high-tech industries. In recent decades, China has made sustained investments in its domestic high-tech industries, with the goal of increasing their productivity. This paper investigates the effect of this investment on relative R&D efficiency across China's high-tech sectors. Data Envelopment Analysis (DEA) was used to generate quantitative indices for sector comparisons. The analysis of this study indicates that overall R&D investment efficiency did not increase from 1998 to 2009, despite R&D expenditure increasing by 2188%. Over the same period, most sectors suffered from decreasing returns to scale (DRS), presumably also reflecting the inefficient R&D investment. Most of the sectors showed significant fluctuation on R&D investment efficiency. This research result indicates that the problem of China's high-tech industry may be from the inefficiency of its technology commercialization processes, and therefore represents a critical parameter for policy makers and managers.