Predicting Pair Success in a Pair Programming Eye Tracking Experiment Using Cross-Recurrence Quantification Analysis

Pair programming is a model of collaborative learning. It has become a well-known pedagogical practice in teaching introductory programming courses because of its potential benefits to students. This study aims to investigate pair patterns in the context of pair program tracing and debugging to determine what characterizes collaboration and how these patterns relate to success, where success is measured in terms of performance task scores. This research used eye-tracking methodologies and techniques such as cross-recurrence quantification analysis. The potential indicators for pair success were used to create a model for predicting pair success. Findings suggest that it is possible to create a model capable of predicting pair success in the context of pair programming. The predictors for the pair success model that can obtain the best performance are the pairs\u27 proficiency level and degree of acquaintanceship. This was achieved using an ensemble algorithm such as Gradient Boosted Trees. The performance of the pairs is largely determined by the proficiency level of the individuals in the pairs; hence, it is recommended that the struggling students be paired with someone who is considered proficient in programming and with whom the struggling student is comfortable working with

The Impact of Extreme Weather on Student Online Learning Participation

In March 2020, the COVID-19 pandemic forced over 1 billion learners to shift from face-to-face instruction to online learning. Seven months after it began, this transition became even more challenging for Filipino online learners. Eight typhoons struck the Philippines from October to November 2020. Two of these typhoons caused widespread flooding, utilities interruptions, property destruction, and loss of life. We examine how these severe weather conditions affected online learning participation of Filipino students pursuing their undergraduate and graduate studies. We used CausalImpact analysis to explore September 2020 to January 2021 data collected from the Moodle Learning Management System data of one university in the Philippines. We found that overall student online participation was significantly negatively affected by typhoons. However, the effect on participation in Assignments and Quizzes was not significant. These findings suggested that students continued to participate in activities that have a direct bearing on their final grades, rather than activities that had no impact on their course outcomes

Carelessness and Affect in an Intelligent Tutoring System for Mathematics

We investigate the relationship between students’ affect and their frequency of careless errors while using an Intelligent Tutoring System for middle school mathematics. A student is said to have committed a careless error when the student’s answer is wrong despite knowing the skill required to provide the correct answer. We operationalize the probability that an error is careless through the use of an automated detector, developed using educational data mining, which infers the probability that an error involves carelessness rather than not knowing the relevant skill. This detector is then applied to log data produced by high-school students in the Philippines using a Cognitive Tutor for scatterplots. We study the relationship between carelessness and affect, triangulating between the detector of carelessness and field observations of affect. Surprisingly, we find that carelessness is common among students who frequently experience engaged concentration. This finding implies that a highly engaged student may paradoxically become overconfident or impulsive, leading to more careless errors. In contrast, students displaying confusion or boredom make fewer careless errors. Further analysis over time suggests that confused and bored students have lower learning overall. Thus, their mistakes appear to stem from a genuine lack of knowledge rather than carelessness

A Framework of Exercise Recommendation for Novice Learners in Computer Programming

To support novice learners majoring in Information Technology, this paper proposed an ontology-based framework to recommend exercise to learners in response to their understanding levels. This framework involves three essential mechanisms: (1) determination of the level of exercise, (2) evaluation of learner's understanding, and (3) recommendation of exercise. The prototype system will be implemented to enable the instructors to add or edit exercises based on 60 questions with solutions covering 20 topics of introductory programming which are initially determined by this research

Carelessness and Affect in an Intelligent Tutoring System for Mathematics

We investigate the relationship between students' affect and their frequency of careless errors while using an Intelligent Tutoring System for middle school mathematics. A student is said to have committed a careless error when the student's answer is wrong despite knowing the skill required to provide the correct answer. We operationalize the probability that an error is careless through the use of an automated detector, developed using educational data mining, which infers the probability that an error involves carelessness rather than not knowing the relevant skill. This detector is then applied to log data produced by high-school students in the Philippines using a Cognitive Tutor for scatterplots. We study the relationship between carelessness and affect, triangulating between the detector of carelessness and field observations of affect. Surprisingly, we find that carelessness is common among students who frequently experience engaged concentration. This finding implies that a highly engaged student may paradoxically become overconfident or impulsive, leading to more careless errors. In contrast, students displaying confusion or boredom make fewer careless errors. Further analysis over time suggests that confused and bored students have lower learning overall. Thus, their mistakes appear to stem from a genuine lack of knowledge rather than carelessness

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Non-typeable Haemophilus influenzae and Streptococcus pneumoniae as primary causes of acute otitis media in colombian children: a prospective study

<p>Abstract</p> <p>Background</p> <p>Acute otitis media (AOM) is one of the most frequently encountered bacterial infections in children aged < 5 years; <it>Streptococcus pneumoniae </it>(<it>S. pneumoniae</it>) and non-typeable <it>Haemophilus influenzae </it>(NTHi) are historically identified as primary AOM causes. Nevertheless, recent data on bacterial pathogens causing AOM in Latin America are limited. This prospective study aimed to identify and characterize bacterial etiology and serotypes of AOM cases including antimicrobial susceptibility in < 5 year old Colombian children.</p> <p>Methods</p> <p>From February 2008 to January 2009, children ≥3 months and < 5 years of age presenting with AOM and for whom a middle ear fluid (MEF) sample was available were enrolled in two medical centers in Cali, Colombia. MEF samples were collected either by tympanocentesis procedure or spontaneous otorrhea swab sampling. Bacteria were identified using standard laboratory methods, and antimicrobial resistance testing was performed based on the 2009 Clinical and Laboratory Standards Institute (CLSI) criteria. Most of the cases included in the study were sporadic in nature.</p> <p>Results</p> <p>Of the 106 enrolled children, 99 were included in the analysis. Bacteria were cultured from 62/99 (63%) of samples with <it>S. pneumoniae, H. influenzae, or S. pyogenes</it>. The most commonly isolated bacteria were <it>H. influenzae </it>in 31/99 (31%) and <it>S. pneumoniae </it>in 30/99 (30%) of samples. The majority of <it>H. influenzae </it>episodes were NTHi (27/31; 87%). 19F was the most frequently isolated pneumococcal serotype (10/30; 33%). Of the 30 <it>S. pneumoniae </it>positive samples, 8/30 (27%) were resistant to tetracycline, 5/30 (17%) to erythromycin and 8/30 (27%) had intermediate resistance to penicillin. All <it>H. influenzae </it>isolates tested were negative to beta-lactamase.</p> <p>Conclusions</p> <p>NTHi and <it>S. pneumoniae </it>are the leading causes of AOM in Colombian children. A pneumococcal conjugate vaccine that prevents both pathogens could be useful in maximizing protection against AOM.</p