ArAl: An Online Tool for Source Code Snapshot Metadata Analysis

© 2019 Association for Computing Machinery. Several systems that collect data from students' problem solving processes exist. Within computing education research, such data has been used for multiple purposes, ranging from assessing students' problem solving strategies to detecting struggling students. To date, however, the majority of the analysis has been conducted by individual researchers or research groups using case by case methodologies. Our belief is that with increasing possibilities for data collection from students' learning process, researchers and instructors will benefit from ready-made analysis tools. In this study, we present ArAl, an online machine learning based platform for analyzing programming source code snapshot data. The benefit of ArAl is two-fold. The computing education researcher can use ArAl to analyze the source code snapshot data collected from their own institute. Also, the website provides a collection of well-documented machine learning and statistics based tools to investigate possible correlation between different variables. The presented web-portal is available at online-analysisdemo. herokuapp.com. This tool could be applied in many different subject areas given appropriate performance data

Syntax error based quantification of the learning progress of the novice programmer

© 2018 Association for Computing Machinery. Recent data-driven research has produced metrics for quantifying a novice programmer’s error profile, such as Jadud’s error quotient. However, these metrics tend to be context dependent and contain free parameters. This paper reviews the caveats of such metrics and proposes a more general approach to developing a metric. The online implementation of the proposed metric is publicly available at http://online-analysis-demo.herokuapp.com/

IAGNOSTIC VALUE OF MAGNETIC RESONANCE SPECTROSCOPY IN MORPHOMETRICAL ANALYSIS OF BASAL GANGLIA IN PATIENTS WITH IDIOPATHIC GENERALIZED EPILEPSY‏

Idiopathic generalized epilepsy (IGE) is a kind of epilepsy that has tonic-colonic characteristic and myocolonic tensions and its clinical symptom starts from the first 20 years of the life. Proton magnetic resonance spectroscopy (H1-MRS) technique applies as a noninvasive procedure to find metabolic disorders by evaluating brain metabolites. Purpose of this study was to determine efficacy of the MRS in thalamus imaging of patients with IGE. Applying H1-MRS (technique: PRESS-CSI], we evaluated thalamus images of 63 people (35 controls: 23 males, 12 females, ranging in age 19-46 years, average: 34.8±0.62 years) and 28 IGE patients (10 males, 18 females, ranging in age 20-49 years, average: 37.4±1.04 years). The data analyzed by SPSS (v.20]. Comparing the average NAA/Cr for the right thalamus, a significant reduction was seen between the control group and the IGE patients (p<0.0001]. Likewise, for the left thalamus, the NAA/Cr was significantly decreased when we compared it for the control group and the IGE patients (p<0.001). H1-MRS could be a suitable diagnostic technique to evaluate epilepsy in IGE patients. The possible alteration of neuronal pathways in the thalamo-cortical circuit seems to play a critical role in epileptogenesis of IGE

Exploring machine learning methods to automatically identify students in need of assistance

Copyright 2015 ACM. Methods for automatically identifying students in need of assistance have been studied for decades. Initially, the work was based on somewhat static factors such as students' educational background and results from various questionnaires, while more recently, constantly accumulating data such as progress with course assignments and behavior in lectures has gained attention. We contribute to this work with results on early detection of students in need of assistance, and provide a starting point for using machine learning techniques on naturally accumulating programming process data. When combining source code snapshot data that is recorded from students' programming process with machine learning methods, we are able to detect high- and low-performing students with high accuracy already after the very first week of an introductory programming course. Comparison of our results to the prominent methods for predicting students' performance using source code snapshot data is also provided. This early information on students' performance is beneficial from multiple viewpoints. Instructors can target their guidance to struggling students early on, and provide more challenging assignments for high-performing students. Moreover, students that perform poorly in the introductory programming course, but who nevertheless pass, can be monitored more closely in their future studies

Learning Programming, Syntax Errors and Institution-specific Factors

Learning programming is a road that is paved with mistakes. Initially, novices are bound to write code with syntactic mistakes, but after a while semantic mistakes take a larger role in the novice programmers’ lives. Researchers who wish to understand that road are increasingly using data recorded from students’ programming processes. Such data can be used to draw inferences on the typical errors, and on how students approach fixing them. At the same time, if the lens that is used to analyze such data is used only from one angle, the view is likely to be narrow. In this work, we replicate a previous multi-institutional study by Brown et al. [5]. That study used a large scale programming process data repository to analyze mistakes that novices make while learning programming. In our single institution replication of that study, we use data collected from approximately 800 students. We investigate the frequency, time required to fix, and the development of mistakes through the semester. We contrast our findings from our single institution with the multi-institutional study, and show that whilst the data collection tools and the research methodology are the same, the results can differ solely due to how the course is conducted

Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success

© 2016 ACM. The computing education community has studied extensively the errors of novice programmers. In contrast, little attention has been given to student's mistake in writing SQL statements. This paper represents the first large scale quantitative analysis of the student's syntactic mistakes in writing different types of SQL queries. Over 160 thousand snapshots of SQL queries were collected from over 2000 students across eight years. We describe the most common types of syntactic errors that students make. We also describe our development of an automatic classifier with an overall accuracy of 0.78 for predicting student performance in writing SQL queries

Lipid oxidation in fresh and stored eggs enriched with dietary w3 and w6 polyunsaturated fatty acids and vitamin E and A dosages

Two experiments were planned to study the influence of dietary fat sources (fish oil (FO) or sunflower oil (SO)) and dietary doses of -tocopheryl acetate (-TA) (0, 60 and 120 mg/kg of feed) and vitamin A (0 IU, 10000 IU and 20000 IU) on lipid oxidation of stored eggs in three stages of 0 or fresh, 1 and 2 months of storage time. In the first experiment, 96 hen layers in six treatments including two oil sources (FO and SO) and two dietary [0, 60 and 120 mg/kg doses of -tocopheryl acetate (-TA)] were fed for 75 days. In the second experiment, 96 hen layers in six treatments including two sources of w3 and w6 (FO and SO) and three doses 0, 10000 and 20000 IU of vitamin A were fed for 75 days. The results showedthat using -TA supplementation, lipid stability of enriched eggs increased and was very effective throughout the stored period of the eggs. Yolk TBA value was higher in fish oil than sunflower oil groups (p &lt; 0.01). The treatments that contained 120 mg/kg of -TA in diets, showed lower lipidperoxidation than other groups in stages of 2 and 3 storage time (30 and 60 days). The degree of lipid oxidation in fresh, 1 and 2 months of storage eggs was measured by the lipid TBA values. The results showed that TBA value in fresh and stored eggs was higher in groups containing fish oil than other groups (p &lt; 0.01). The MDA value in stage 1 was higher in fish oil group and in 2 and 3 stages was lower in FO + A1. Therefore, addition of Vitamin E and A as natural antioxidants in diets containing oil source for the prevention of lipid oxidation is recommended

Noninvasive Stem Cell Labeling Using USPIO Technique and their Detection with MRI

Background: To date, several imaging techniques to track stem cells are used such as positron emission tomography (PET), single photon emission computed tomography (SPECT), Bioluminescence imaging (BLI), fluorescence imaging, CT scan and magnetic resonance imaging (MRI). Although, overall sensitivity of MRI compared to SPECT and Bioluminescence techniques are lower, but due to high spatial resolution (~100 mm), long term three-dimensional imaging capability, in vivo quick access to images in three different sections, and noninvasiveness it is being used as the method of choice. Methods: The present study is the search results for authors and sources of information in the field of molecular and cellular imaging to examine the problems and perspectives about stem cells labeling with Ultrasmall Super Paramagnetic Iron Oxide (USPIO) and their tracking by MRI. Results: With the advancement of technology, including quantum physics, chemistry, and computer software, MRI with an excellent spatial resolution and contrast, is surpasses other imaging modalities in the analysis of anatomical and pathological features and images of all body tissues. From the other side, advances in the astronomical science, chemistry and nanotechnology, high biocompatibility and cytotoxicity of nanoparticles, and due to analysis in the metabolic pathways of iron made the procedure easier; however, there are still several fundamental questions in understanding the mechanism of biological molecules in the living cells including: 1- How to detect not only the location but also the performance of the labeled cells? Probably combination of USPIO nanoparticles with other reporter genes as contrast agents for MRI and PET can simultaneously be used to overcome these limitations 2) How to trace stem cells from pre-clinical models to translate to humans? Up to now, due to issues of bioethics, little studies have been done in this area. 3) Whether the transplanted stem cells that have reached the target tissue, will remain or migrate? Despite the fact that cell proliferation and exocytosis are two main factors for long term protection of USPIO nanoparticles inside cells, their signals cannot be received for a long time. 4) What mechanisms cause stem cells reaching the target tissue to react with their environment? And 5) what is the number of transplanted cells in live tissue, and what is their half-life? Conclusion: This study showed that USPIO nanoparticles can enter the cell with a clear dose without any adverse biological effects and could be detected by SWI and T2* techniques under MRI (1.5 Tesla) scanner for almost one month. MRI as a secure mean can illustrate with optimal resolution the spatial-resolution and three-dimensional positions of the stem cells. Keywords: Ultrasmall Super Paramagnetic Iron Oxide (USPIO), labeled stem cell, in vivo tracking, MRI

Consequences of AphanizomenonFlos-aquae(AFA) extract (StemtechTM) on metabolic profile of patients with type 2 diabetes

Background: Blue- green algae is one of the most nutrient dense foods which is rich in substances that have useful effects on human health. The purpose of this study was to evaluate the effectiveness of a water- soluble extract of the cyanophyta Aphanizomenon Flos-aquae (StemtechTM) as a functional supplement on CD markers, lipid profile, glucose levels as well as its side effects in Iranian patients with type 2 diabetes. Methods: During this randomized, double-blind, placebo-controlled trial 49 type 2 diabetic patients, aged between 20 and 60years with a HbA1C�7.5, were allocated. Patients were divided into two groups of placebo and treated with an equal ratio 1:1. The subjects in StemtechTM group received one capsule of StemFlo (508mg) before breakfast and two capsules of StemEnhance (500mg) after each meal for a period of 12weeks, and placebo group was instructed to take placebo with the same pattern. During the intervention period, subjects were asked to keep usual diet and prohibited to take any functional foods or dietary supplements. Metabolic panel has been measured as the primary outcome of study at the beginning and end of the intervention period via blood sampling. Results: StemtechTM supplementation for 12weeks decreased fasting blood glucose (FBG) and Glycatedhemoglobin (HbA1c). Mean serum chemistry parameters (Triglyceride, Total Cholesterol, LDL, HDL, CRP, AST, ALT, BUN and Creatinine) as well as CD 34+, IL-6, TNF-aα in treated and control groups before and after the study showed no considerable dissimilarities. Conclusion: StemtechTM intervention brought in positive consequence on blood glucose levels in Iranian patients with type 2 diabetes, consequently suggests the StemtechTM as a functional food for the management of diabetes. © 2015 Sanaei et al