The impact of students’ behaviour, their approach, emotions and problem difficulty level on the performance prediction, evaluation and overall learning process during online coding activities

Learning process while solving coding problems is quite complex to understand. It is extremely important to understand the skills which are required and gained during learning to code. As a first step to understand the students’ behaviour and approach during learning coding, two online coding assignments or competitions are conducted with a 1-hour time limit. A survey has been conducted at the end of each coding test and answers to different questions have been collected. In depth statistical analysis is done to understand the learning process while solving the coding problems. It involves lots of parameters including students’ behaviour, their approach and difficulty level of coding problems. The inclusion of mood and emotions related questions can improve overall prediction performance but difficulty level matters in the submission status prediction. Two coding assignments or competitions are analysed through in-depth research on 229 (first coding competition dataset) and 325 (second coding competition dataset) data points. The primary results are promising and these results give in depth insights about how learning to solve coding problems is affected by students’ behaviour, their approach, emotions and problem difficulty level.

Does Mathematics Anxiety Moderate the Effect of Problem Difficulty on Cognitive Effort?

A negative relationship between mathematics anxiety (MA) and mathematics performance is well documented. One suggested explanation for this relationship is that MA interferes with the cognitive processes needed when solving mathematics problems. A demand for using more cognitive effort (e.g., when performing harder mathematics problems), can be traced as an increase in pupil dilation during the performance. However, we lack knowledge of how MA affects this relationship between the problem difficulty and cognitive effort. This study investigated, for the first time, whether MA moderates the effect of arithmetic (i.e., multiplication) problem difficulty on cognitive effort. Thirty-four university students from Norway completed multiplication tasks, including three difficulty levels of problems, while their cognitive effort was also measured by means of pupil dilation using an eyetracker. Further, the participants reported their MA using a questionnaire, and arithmetic competence, general intelligence, and working memory were measured with paper-pencil tasks. A linear mixed model analysis showed that the difficulty level of the multiplication problems affected the cognitive effort, so that the pupil dilated more with harder multiplication problems. However, we did not find a moderating effect of MA on cognitive effort, when controlling for arithmetic competence, general intelligence, and working memory. This suggests that MA does not contribute to cognitive effort when solving multiplication problems.

Predicting Problem Difficulty in Chess

We investigate the question of automatic prediction of task difficulty for humans, of problems that are typically solved through informed search. Our experimental domain is the game of chess. We analyse experimental data from human chess players solving tactical chess problems. The players also estimated the difficulty of these problems. We carried out an experiment with an approach to automatically estimate the difficulty of problems in this domain. The idea of this approach is to use the properties of a “meaningful search tree” to learn to estimate the difficulty of example problems. The construct of a meaningful search tree is an attempt at approximating problem solving by human experts. The learned difficulty classifier was applied to our experimental problems, and the resulting difficulty estimates matched well with the measured difficulties on the Chess Tempo website, and also with the average difficulty perceived by the players.

معاني ألفاظ اليسر والعسر وما يشتق منهما في القرآن الكريم

This study aims to determine the lexical meaning, contextual meaning, and educational implications of the words "yusr" and "'usr" and their derivation in the Qur’an. This research is based on a framework using semantics, namely isytirāk (one word that has many meanings) as a tool to find out the meanings that have implications for the science of education. The research method used is the semantic analysis study by leading to the analysis of the meaning of the word with thematic methods, And the data collection techniques in this study use literature study techniques. After the researcher analyzed the words "yusr" and "’usr" and their derivatives in the Qur'an, it can be concluded that the word "yusr" means easy, to ease, simplify, good deeds, invisible, little/small, gentle, heaven and solution. The word "usr" means distress, difficulty, inability to pay debts, problem difficulty, doomsday, partner differences, ugliness, and hell. The words "yusr" and "'usr" have educational implications that are seen in each of their meanings.

The effects of numeracy and presentation format on judgments of contingency

Covariation information can be used to infer whether a causal link plausibly exists between two dichotomous variables, and such judgments of contingency are central to many critical and everyday decisions. However, individuals do not always interpret and integrate covariation information effectively, an issue that may be compounded by limited numeracy skills, and they often resort to the use of heuristics, which can result in inaccurate judgments. This experiment investigated whether presenting covariation information in a composite bar chart increased accuracy of contingency judgments, and whether it can mitigate errors driven by low numeracy skills. Participants completed an online questionnaire, which consisted of an 11-item numeracy scale and three covariation problems that varied in level of difficulty, involving a fictitious fertilizer and its impact on whether a plant bloomed or not. Half received summary covariation information in a composite bar chart, and half in a 2 × 2 matrix that summarized event frequencies. Viewing the composite bar charts increased accuracy of individuals both high and low in numeracy, regardless of problem difficulty, resulted in more consistent judgments that were closer to the normatively correct value, and increased the likelihood of detecting the correct direction of association. Findings are consistent with prior work, suggesting that composite bar charts are an effective way to improve covariation judgment and have potential for use in the domain of health risk communication.

How Emotions Modulate Arithmetic Performance

The goal of the present study was to test whether and how emotions influence arithmetic performance. Participants had to verify arithmetic problems. True problems were either easier or harder problems. False problems were parity-match or parity-mismatch problems. The odd/even status of proposed and correct answers was the same in parity-match problems (e.g., 19 × 7 = 131) and different in parity-mismatch problems (e.g., 17 × 9 = 152). Before each problem, participants saw a positive (e.g., smiling baby), negative (e.g., mutilations), or neutral pictures (e.g., neutral face) selected from International Affective Picture System (IAPS). They had to decide whether each picture includes a person or not before verifying each arithmetic problem. Results showed different effects of emotion on true- and false problem verification. Participants’ performance on true problems showed decreased problem-difficulty after processing negative pictures and increased difficulty effects after processing positive pictures. On false problems, we found smaller parity-violation effects after negative pictures (i.e., decreased performance on parity-mismatch problems), together with larger parity-violation effects after positive pictures (i.e., decreased performance on parity-match problems). These findings suggest that emotions influence arithmetic performance via which strategy is used and how each strategy is executed on each problem. They have important implications for understanding the role of emotions on arithmetic performance, and more generally on how emotions influence cognition.