Free-and open source software for a course on network management: authoring and enactment of scripts based on collaborative learning strategies

This paper describes a Computer-Supported Collaborative Learning (CSCL) case study in engineering education carried out within the context of a network management course. The case study shows that the use of two computing tools developed by the authors and based on Free- and Open-Source Software (FOSS) provide significant educational benefits over traditional engineering pedagogical approaches in terms of both concepts and engineering competencies acquisition. First, the Collage authoring tool guides and supports the course teacher in the process of authoring computer-interpretable representations (using the IMS Learning Design standard notation) of effective collaborative pedagogical designs. Besides, the Gridcole system supports the enactment of that design by guiding the students throughout the prescribed sequence of learning activities. The paper introduces the goals and context of the case study, elaborates onhow Collage and Gridcole were employed, describes the applied evaluation methodology, anddiscusses the most significant findings derived from the case study.

Teaching motivational interviewing to medical students : a pre-post test pilot study

Objective: To test the efficacy of teaching motivational interviewing (MI) to medical students. Methods: Thirteen 4th year medical students volunteered to participate. Seven days before and 7 days after an 8-hour interactive training MI workshop, each student performed a videorecorded interview with two standardized patients: a 60 year old alcohol dependent woman and a 50 year old cigarette smoking man. Students' counseling skills were coded by two blinded clinicians using the Motivational Interviewing Treatment Integrity 3.0 (MITI). Inter-rater reliability was calculated for all interviews and a test-retest was completed in a sub-sample of 10 consecutive interviews three days apart. Difference between MITI scores before and after training were calculated and tested using non-parametric tests. Effect size was approximated by calculating the probability that posttest scores are greater than pretest scores (P*=P(Pre<Post)+1/2P(Pre=Post)), P*>1/2 indicating greater scores in posttest, P*=1/2 no effect, and P*<1/2 smaller scores in posttest. Results: Median differences between MITI scores before and after MI training indicated a general progression in MI skills: MI spirit global score (median difference=1.5, Inter quartile range=1.5, p<0.001, P*=0.90); Empathy global score (med diff=1, IQR=0.5, p<0.001, P*=0.85); Percentage of MI adherent skills (med diff=36.6, IQR=50.5, p<0.001, P*=0.85); Percentage of open questions (med diff=18.6, IQR=21.6, p<0.001, P*=0.96); reflections/ questions ratio (med diff=0.2, IQR=0.4, p<0.001, P*=0.81). Only Direction global score and the percentage of complex reflections were not significantly improved (med diff=0, IQR=1, p=0.53, P*=0.44, and med diff=4.3, IQR=24.8, p=0.48, P*=0.62, respectively). Inter-rater reliability indicated weighted kappa ranged between 0.14 for Direction to 0.51 for Collaboration and ICC ranged between 0.28 for Simple reflection to 0.95 for Closed question. Test-retests indicated weighted kappa ranged between 0.27 for Direction to 0.80 for Empathy and ICC ranged between 0.87 for Complex reflection to 0.98 for Closed question. Conclusion: This pilot study indicated that an 8-hour training in MI for voluntary 4th year medical students resulted in significant improvement of MI skills. Larger sample of unselected medical students should be studied to generalize the benefit of MI training to medical students. Interrater reliability and test-retests suggested that coders' training should be intensified.

Swain: Stata module to correct the SEM chi-square overidentification test in small sample sizes or complex models. Statistical Software Components S457617, Boston College Department of Economics.

Swain corrects the chi-square overidentification test (i.e., likelihood ratio test of fit) for structural equation models whethr with or without latent variables. The chi-square statistic is asymptotically correct; however, it does not behave as expected in small samples and/or when the model is complex (cf. Herzog, Boomsma, & Reinecke, 2007). Thus, particularly in situations where the ratio of sample size (n) to the number of parameters estimated (p) is relatively small (i.e., the p to n ratio is large), the chi-square test will tend to overreject correctly specified models. To obtain a closer approximation to the distribution of the chi-square statistic, Swain (1975) developed a correction; this scaling factor, which converges to 1 asymptotically, is multiplied with the chi-square statistic. The correction better approximates the chi-square distribution resulting in more appropriate Type 1 reject error rates (see Herzog & Boomsma, 2009; Herzog, et al., 2007).

2005 Annual Report of the Iowa Communications Network

This is the Annual Report for Fiscal Year 2005 (July 1, 2004-June 30, 2005) for the Iowa Communications Network.

Iowa Communications Network Performance Report, FY 2004

Agency Performance Report

Iowa Communications Network Performance Report, FY 2005

Agency Performance Report

Iowa Department of Transportation Report of Savings through use of Iowa Communications Network (ICN), FY 2005

Iowa DOT savings through use of Iowa Communications Network (ICN) videoconferencing

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Effect of Lactobacillus paracasei ST11 on a nasal provocation test with grass pollen in allergic rhinitis.

Cite this as: J. Wassenberg, S. Nutten, R. Audran, N. Barbier, V. Aubert, J. Moulin, A. Mercenier and F. Spertini, Clinical & Experimental Allergy, 2011 (41) 565-573. SUMMARY: Background Probiotics have been associated with prevention and improvement of symptoms in atopic diseases such as atopic dermatitis. However, few studies exist that document their efficacy for upper airways allergies such as allergic rhinitis. Objective To investigate the effect of short-term oral administration of Lactobacillus paracasei ST11 on a nasal provocation test (NPT) with grass pollen. Methods Thirty-one adult volunteers with allergic rhinitis were enrolled in a randomized, double-blind, placebo-controlled study, based on two 4-week cross-over periods of product consumption (ST11-fermented milk vs. placebo), separated by a wash-out period of 6-8 weeks. Objective and subjective clinical parameters of NPT as well as systemic and nasal immunological parameters were compared between the two treatment periods (registration number: NCT 011 50 253). Results Subjects that received ST11-fermented milk had lower nasal congestion than subjects under placebo (visual analogical scale; P<0.05). Nasal pruritus followed the same trend. However, no significant change in combined nasal reaction threshold was observed between the two periods. IL-5 secretion by peripheral blood mononuclear cells and serum allergen-specific IgG4 were significantly lower in ST11-fermented milk group compared to placebo group. IL-8 and IL-10 secretion followed the same trend. Conclusion and Clinical Relevance Short-term treatment with ST11-fermented milk before NPT significantly improved a clinical marker of NPT (subjective nasal congestion) and down-regulated systemic immune markers (IL-5 from peripheral blood mononuclear cells and serum IgG4). These data strongly suggest that probiotics may down modulate key parameters of allergic rhinitis and warrant future evaluation in seasonal trials.