Investigating social media addiction and impact of social media addiction, loneliness, depression, life satisfaction and problem-solving skills on academic self-efficacy and academic success among university students.

Introduction: The negative effects of post-COVID-19 restrictions have been detected in students' mental well-being due to internet addiction, changing habits, despair and uncertainty. Students' academic success is expected to be affected by social media addiction, loneliness, depression, life satisfaction, problem solving skills and academic self-efficacy factors. This study aimed to determine the level of social media addiction and the effects of these factors on the academic success of university students and define their interactions with each other. Methods: Four hundred nineteen questionnaires were collected between October-December 2022 at Bingöl University, Türkiye. Descriptive statistics, independent t-test, One-Way ANOVA, correlation and multiple linear regression methods were used to analyze data with the help of the SPSS 22 software. Results: Middle level grade (GPA) average (71,17 ± 9,69 out of 100), low level social support from friends and family members (34,6%), spending more than 4 h on social media (42,5%), middle level social media addiction, moderate depression level (51,31%-PHQ > 10), mild loneliness and slight dissatisfaction with life were found among students. Furthermore, high academic self-efficacy, moderate agreement with academic performance and good problem-solving skills were indicated in the survey results. Significant differences, such as higher life satisfaction among males and higher depression among females, were measured. Academic self-efficacy scale, problem solving skills and satisfaction with life had a negative correlation with social media addiction and depression, while a positive correlation with academic performance measures. Problem solving skills, satisfaction with life, fourth class vs. others and living alone vs. others were positive predictors of the academic self-efficacy. Meanwhile, loneliness was a negative predictor of the academic self-efficacy, while higher problem-solving skills and being female were positive factors leading to a higher GPA. Discussion: The fact that the participants were only students from Bingöl University limits the ability to generalize the results. Policymakers could implement social and problem-solving skills training to develop better academic programs and cognitive-behavioral therapy for students' academic success.

Messy but worth it: human-centred design as applied within a successful vaccine-promotive campaign.

Human-centred design (HCD) is an approach to problem-solving that prioritises understanding and meeting the needs of the end-users. Researchers and designers practice empathic listening as users share their perspectives, thereby enabling a variety of stakeholders to cocreate effective solutions. While a valuable and, in theory, straightforward process, HCD in practice can be chaotic: Practitioners often struggle to navigate an excess of (often conflicting) ideas and to strike a balance between problem-understanding and problem-solving. In this practice paper, we outline our own experiences with HCD, which ultimately resulted in the development of a successful video-based intervention to bolster vaccine confidence in the Philippines. We highlight the use of 'radical circles' to overcome roadblocks and navigate tensions. Radical circles entail groups of individuals with divergent opinions and identities engaging in critical analysis of a given idea, actively challenging standard ways of thinking, and ultimately, generating solutions. Employing radical circles enabled us to innovate and adapt to new perspectives that emerged along the non-linear HCD pathway. Our incorporation of radical circles into HCD methodology demonstrates its potential as a powerful complementary step in the meaning-making process. In our view, radical circles could enrich HCD processes and provide a solution to design overcrowding, leading to meaningful, transformative and successful interventions.

Learners' Spontaneous Gesture Before a Math Lesson Predicts the Efficacy of Seeing Versus Doing Gesture During the Lesson.

Gestures-hand movements that accompany speech and express ideas-can help children learn how to solve problems, flexibly generalize learning to novel problem-solving contexts, and retain what they have learned. But does it matter who is doing the gesturing? We know that producing gesture leads to better comprehension of a message than watching someone else produce gesture. But we do not know how producing versus observing gesture impacts deeper learning outcomes such as generalization and retention across time. Moreover, not all children benefit equally from gesture instruction, suggesting that there are individual differences that may play a role in who learns from gesture. Here, we consider two factors that might impact whether gesture leads to learning, generalization, and retention after mathematical instruction: (1) whether children see gesture or do gesture and (2) whether a child spontaneously gestures before instruction when explaining their problem-solving reasoning. For children who spontaneously gestured before instruction, both doing and seeing gesture led to better generalization and retention of the knowledge gained than a comparison manipulative action. For children who did not spontaneously gesture before instruction, doing gesture was less effective than the comparison action for learning, generalization, and retention. Importantly, this learning deficit was specific to gesture, as these children did benefit from doing the comparison manipulative action. Our findings are the first evidence that a child's use of a particular representational format for communication (gesture) directly predicts that child's propensity to learn from using the same representational format.

Relationship Between Prone Skills and Motor-Based Problem-Solving Abilities in Full-Term and Preterm Infants During the First 6 Months of Life.

Motor experiences shape cognitive development in infancy, with the prone position being one such crucial motor experience in the first 6 months of life. Although the motor benefits of the prone position are well-documented, its influence on early cognitive abilities remains insufficiently explored. This study quantified the relationship between prone motor skills and motor-based problem-solving abilities in 48 full-term and preterm infants aged 3-6 months. Prone skills were assessed using the Alberta Infant Motor Scale's prone domain. The Assessment of Problem-Solving in Play was utilized to measure motor-based problem-solving by observing how motor actions were used to solve toys. Advanced prone motor skills were correlated with an increase in sophisticated exploration skills and a concurrent decline in lower order exploration skills in all infants, with correlations being stronger in preterm infants. Notably, a 1-point increase in prone skills was associated with a 1.3-point increase in total motor-based problem-solving abilities in all infants. Our findings provide preliminary evidence for the contribution of prone play to cognitive development in infants, prompting considerations for assessment and intervention strategies. Further research is needed to ascertain if the delayed acquisition of prone motor skills is indicative of poor early problem-solving abilities in preterm infants.

Are comparable studies really comparable? Suggestions from a problem-solving experiment on urban and rural great tits.

Performance in tests of various cognitive abilities has often been compared, both within and between species. In intraspecific comparisons, habitat effects on cognition has been a popular topic, frequently with an underlying assumption that urban animals should perform better than their rural conspecifics. In this study, we tested problem-solving ability in great tits Parus major, in a string-pulling and a plug-opening test. Our aim was to compare performance between urban and rural great tits, and to compare their performance with previously published problem solving studies. Our great tits perfomed better in string-pulling than their conspecifics in previous studies (solving success: 54%), and better than their close relative, the mountain chickadee Poecile gambeli, in the plug-opening test (solving success: 70%). Solving latency became shorter over four repeated sessions, indicating learning abilities, and showed among-individual correlation between the two tests. However, the solving ability did not differ between habitat types in either test. Somewhat unexpectedly, we found marked differences between study years even though we tried to keep conditions identical. These were probably due to small changes to the experimental protocol between years, for example the unavoidable changes of observers and changes in the size and material of test devices. This has an important implication: if small changes in an otherwise identical set-up can have strong effects, meaningful comparisons of cognitive performance between different labs must be extremely hard. In a wider perspective this highlights the replicability problem often present in animal behaviour studies.

Wild raccoons demonstrate flexibility and individuality in innovative problem-solving.

Cognitive skills, such as innovative problem-solving, are hypothesized to aid animals in urban environments. However, the significance of innovation in wild populations, and its expression across individuals and socio-ecological conditions, is poorly understood. To identify how and when innovation arises in urban-dwelling species, we used advanced technologies and new testing and analytical methods to evaluate innovative problem-solving abilities of wild raccoons (Procyon lotor). We deployed multi-compartment puzzle boxes with either one or multiple solution types and identified raccoons using radio frequency identification. Raccoons solved these novel extractive foraging tasks, and their success was influenced by age and exploratory diversity. Successful raccoons always discovered multiple different solution types, highlighting flexible problem-solving. Using a unique, comparative sequence analysis approach, we found that variation in raccoon solving techniques was greater between individuals than within individuals, and this self-similarity intensified during times of competition. Finally, the inclusion of an easier solution in the multi-solution trials enabled previously unsuccessful raccoons to bootstrap their learning and successfully open multiple difficult solutions. Our study suggests that innovative problem-solving is probably influenced by many factors and has provided novel field and analytical methods, as well as new insights on the socio-ecological dynamics of urban populations.

Effectiveness of spaced repetition for clinical problem solving amongst undergraduate medical students studying paediatrics in Pakistan.

BACKGROUND: Studies using spaced repetition for teaching and learning in undergraduate clinical rotations such as paediatrics are limited, even more so in the South Asian region. Therefore, this study aimed to identify the effectiveness of utilizing spaced repetition compared to traditional learning methods among undergraduate medical students during their paediatric rotation at a medical university in Pakistan. METHODS: Bahria University Medical and Dental College (BUMDC) conducted quasii-experimental research in Karachi. Four topics were identified from the Year 5 Pediatrics curriculum to be used in the study, using which the study content was developed along with 50 multiple choice questions (MCQs) for assessment. All BUMDC Year 5 medical students rotating in Pediatrics were included and randomly allocated to the control or intervention group. In the control group, they provided the students with traditional study methods consisting of books and lectures to learn topics. In the intervention group, we created an Anki flashcard deck of the same topics to enable learning via spaced repetition. The researchers conducted a pretest and post test assessment of the 50 MCQs in both groups at the beginning and after the four-week study interval. The data were analysed using SPSS 19. RESULTS: A total of 115 BUMDC medical students agreed to participate in the study; 70 (59.1%) were in the intervention group, and 45 (41.7%) were in the control group. The pretest mean score of the control group was 27.96 ± 3.70, and the posttest mean score was 27.22 ± 5.02, with no statistically significant difference at the 95% confidence level. The mean score of the pretest for the intervention group was 27.93 ± 4.53, and that of the posttest was 30.8 ± 4.56, with a statistically significant difference at the 95% confidence level. The intervention showed a significant effect size of 0.8. CONCLUSION: The use of spaced repetitions resulted in significantly greater scores for medical students studying paediatrics than for those using more traditional methods of learning, compromising medical books and lectures. Considering that medical students need to retain a vast amount of information, using spaced repetition through flashcards can be a more effective learning tool that is more cost-efficient and time-efficient than traditional learning methods.

Involving Parents in Cognitive Behavioral Therapy for Children and Adolescents with Conduct Problems: Goals, Outcome Expectations, and Normative Beliefs About Aggression are Targeted in Sessions with Parents and Their Child.

Children and adolescents with conduct problems participate in Cognitive Behavioral Therapy (CBT), either in individual or group format, in view of learning social problem-solving skills that enable them to behave in more independent and situation-appropriate ways. Parents must support their child's learning processes in everyday life and therefore these processes need attention in CBT sessions in which parents and their child participate. The social problem-solving model of CBT previously described (Matthys & Schutter, Clin Child Fam Psychol Rev 25:552-572, 2022; Matthys & Schutter, Clin Child Fam Psychol Rev 26:401-415, 2023) consists of nine psychological skills. In this narrative review we propose that instead of addressing each skill separately in sessions with both parents and their child, therapists work on three schemas (latent mental structures): (1) goals, (2) outcome expectations, and (3) normative beliefs about aggression. Based on social-cognitive and cognitive neuroscience studies we argue that these three schemas affect five core social problem-solving skills: (1) interpretation, (2) clarification of goals, (3) generations of solutions, (4) evaluation of solutions, and (5) decision-making. In view of tailoring CBT to the individual child's characteristic schemas and associated social problem-solving skills, we suggest that children and adolescents participate in individual sessions with their parents. The therapist uses Socratic questioning in order to find out characteristic schemas of the child, encourage reflection on these schemas, and explore alternative schemas that had previously been outside the child's attention. The therapist functions as a model for parents to ask their child questions about the relevant schemas with a view of achieving changes in the schemas.

Comparing First-Year Engineering Student Conceptions of Ethical Decision-Making to Performance on Standardized Assessments of Ethical Reasoning.

The Defining Issues Test 2 (DIT-2) and Engineering Ethical Reasoning Instrument (EERI) are designed to measure ethical reasoning of general (DIT-2) and engineering-student (EERI) populations. These tools-and the DIT-2 especially-have gained wide usage for assessing the ethical reasoning of undergraduate students. This paper reports on a research study in which the ethical reasoning of first-year undergraduate engineering students at multiple universities was assessed with both of these tools. In addition to these two instruments, students were also asked to create personal concept maps of the phrase "ethical decision-making." It was hypothesized that students whose instrument scores reflected more postconventional levels of moral development and more sophisticated ethical reasoning skills would likewise have richer, more detailed concept maps of ethical decision-making, reflecting their deeper levels of understanding of this topic and the complex of related concepts. In fact, there was no significant correlation between the instrument scores and concept map scoring, suggesting that the way first-year students conceptualize ethical decision making does not predict the way they behave when performing scenario-based ethical reasoning (perhaps more situated). This disparity indicates a need to more precisely quantify engineering ethical reasoning and decision making, if we wish to inform assessment outcomes using the results of such quantitative analyses.

Deliberate Problem-solving with a Large Language Model as a Brainstorm Aid Using a Checklist for Prompt Generation.

Large language models (LLMs) use autoregression to generate text in response to queries. Crafting an appropriate prompt to elicit the desired response from these generative artificial intelligence (AI) models to solve a clinical problem can be a challenge to clinicians who may be unfamiliar with this technology. The use of checklists to generate carefully worded queries can leverage the potential of LLMs as a brainstorming aid for medical problem-solving. Systematically using different prompts to generate the most appropriate differential diagnoses for selected clinical case scenarios, a potential checklist for prompt generation has been created and is reported here.

Reasoning More Efficiently with Primary Knowledge Despite Extraneous Cognitive Load.

Geary's evolutionary approach in educational psychology differentiates between primary (low cognitive costs and motivational advantage) and secondary knowledge (high cognitive costs and no motivational benefit). Although these features have been well demonstrated in previous work, the underlying mechanisms remain unclear. To investigate it, in a reasoning task, the present study varies (i) the content of the problems (primary knowledge vs. secondary; e.g., food vs. grammar rules), (ii) the intrinsic cognitive load (conflict or non-conflict syllogism, the former requiring more cognitive resources to be properly processed than the latter) and (iii) the extraneous cognitive load (via a Dot Memory Task with three modalities: low, medium and high cognitive load). Analyses assessed the influence of these variables on performance, problem solving speed and perceived cognitive load. Results confirmed the positive impact of primary knowledge on efficiency, particularly when intrinsic cognitive load was high. Surprisingly, the extraneous cognitive load did not influence the performance in secondary knowledge content but that in primary knowledge content: the higher the additional load was, the better the performance was, only for primary knowledge and especially for syllogisms with high intrinsic load. Findings support evolutionary theory as secondary knowledge would overload cognitive resources, preventing participants from allocating sufficient resources to solve problems. Primary knowledge would allow participants to process the additional load and to increase their performance despite this. This study also raises the hypothesis that a minimum cognitive load is necessary for participants to be invested in the task.

External constraints that led to physiology lab improvements.

The modifications were in response to changing constraints, including time, money, space, student background, and my knowledge and comfort. The lab went from emphasizing experiments with the attendant troubleshooting and data analysis skills to a lab focused more on giving prehealth professional students the motivation to learn physiology problem-solving skills by providing real cases. In the lab, students watched and listened to a random student try to use these problem-solving skills to solve the problem. This made them appreciate how much others also struggle in solving the problem. Some students with imposter syndrome think their classmates immediately know how to solve a problem, and therefore, seeing others also struggle has the potential to reduce imposter syndrome. Rather than having the students do experiments, they did kinesthetic activities with mechanical models to generate data without biological variation. They then graphed their data, thus improving their ability to actually read graphs rather than memorize patterns.NEW & NOTEWORTHY I learned to explicitly recognize the current and projected constraints of instructor comfort, money, space, student background (poor graph reading and problem-solving skills), student safety, and time and energy on the possible goals and methods to attain them for an undergraduate physiology lab. I cannot decide if changing constraints allowed me to reexamine my goals or whether it forced me to reexamine my goals. In either case, the reexamination of my goals (and their priorities), within the context of the constraints, allowed me to redesign the labs to better meet my new goals within this new context.

Arithmetic fluency and number processing skills in identifying students with mathematical learning disabilities.

BACKGROUND: Students with mathematical learning disabilities (MLD) struggle with number processing skills (e.g., enumeration and number comparison) and arithmetic fluency. Traditionally, MLD is identified based on arithmetic fluency. However, number processing skills are suggested to differentiate low achievement (LA) from MLD. AIMS: This study investigated the accuracy of number processing skills in identifying students with MLD and LA, based on arithmetic fluency, and whether the classification ability of number processing skills varied as a function of grade level. METHODS AND PROCEDURES: The participants were 18,405 students (girls = 9080) from Grades 3-9 (ages 9-15). Students' basic numerical skills were assessed with an online dyscalculia screener (Functional Numeracy Assessment -Dyscalculia Battery, FUNA-DB), which included number processing and arithmetic fluency as two factors. OUTCOMES AND RESULTS: Confirmatory factor analyses supported a two-factor structure of FUNA-DB. The two-factor structure was invariant across language groups, gender, and grade levels. Receiver operating characteristics curve analyses indicated that number processing skills are a fair classifier of MLD and LA status across grade levels. The classification accuracy of number processing skills was better when predicting MLD (cut-off < 5 %) compared to LA (cut-off < 25 %). CONCLUSIONS AND IMPLICATIONS: Results highlight the need to measure both number processing and arithmetic fluency when identifying students with MLD.

Evaluating language models for mathematics through interactions.

There is much excitement about the opportunity to harness the power of large language models (LLMs) when building problem-solving assistants. However, the standard methodology of evaluating LLMs relies on static pairs of inputs and outputs; this is insufficient for making an informed decision about which LLMs are best to use in an interactive setting, and how that varies by setting. Static assessment therefore limits how we understand language model capabilities. We introduce CheckMate, an adaptable prototype platform for humans to interact with and evaluate LLMs. We conduct a study with CheckMate to evaluate three language models (InstructGPT, ChatGPT, and GPT-4) as assistants in proving undergraduate-level mathematics, with a mixed cohort of participants from undergraduate students to professors of mathematics. We release the resulting interaction and rating dataset, MathConverse. By analyzing MathConverse, we derive a taxonomy of human query behaviors and uncover that despite a generally positive correlation, there are notable instances of divergence between correctness and perceived helpfulness in LLM generations, among other findings. Further, we garner a more granular understanding of GPT-4 mathematical problem-solving through a series of case studies, contributed by experienced mathematicians. We conclude with actionable takeaways for ML practitioners and mathematicians: models that communicate uncertainty, respond well to user corrections, and can provide a concise rationale for their recommendations, may constitute better assistants. Humans should inspect LLM output carefully given their current shortcomings and potential for surprising fallibility.

KRAGEN: a knowledge graph-enhanced RAG framework for biomedical problem solving using large language models.

MOTIVATION: Answering and solving complex problems using a large language model (LLM) given a certain domain such as biomedicine is a challenging task that requires both factual consistency and logic, and LLMs often suffer from some major limitations, such as hallucinating false or irrelevant information, or being influenced by noisy data. These issues can compromise the trustworthiness, accuracy, and compliance of LLM-generated text and insights. RESULTS: Knowledge Retrieval Augmented Generation ENgine (KRAGEN) is a new tool that combines knowledge graphs, Retrieval Augmented Generation (RAG), and advanced prompting techniques to solve complex problems with natural language. KRAGEN converts knowledge graphs into a vector database and uses RAG to retrieve relevant facts from it. KRAGEN uses advanced prompting techniques: namely graph-of-thoughts (GoT), to dynamically break down a complex problem into smaller subproblems, and proceeds to solve each subproblem by using the relevant knowledge through the RAG framework, which limits the hallucinations, and finally, consolidates the subproblems and provides a solution. KRAGEN's graph visualization allows the user to interact with and evaluate the quality of the solution's GoT structure and logic. AVAILABILITY AND IMPLEMENTATION: KRAGEN is deployed by running its custom Docker containers. KRAGEN is available as open-source from GitHub at: https://github.com/EpistasisLab/KRAGEN.

Inferential reasoning abilities in wild-caught bumblebees.

The ability to make a decision by excluding alternatives (i.e. inferential reasoning) is a type of logical reasoning that allows organisms to solve problems with incomplete information. Several species of vertebrates have been shown to find hidden food using inferential reasoning abilities. Yet little is known about invertebrates' logical reasoning capabilities. In three experiments, I examined wild-caught bumblebees' abilities to locate a 'rewarded' stimulus using direct information or incomplete information-the latter requiring bees to use inferential reasoning. To do so, I adapted three paradigms previously used with primates-the two-cup, three-cup and double two-cup tasks. Bumblebees saw either two paper strips (experiment 1), three paper strips (experiment 2) or two pairs of paper strips (experiment 3) and experienced one of them being rewarded or unrewarded. At the test, they could choose between two (experiment 1), three (experiment 2) or four paper strips (experiment 3). Bumblebees succeeded in the three tasks and their performance was consistent with inferential reasoning. These findings highlight the importance of comparative studies with invertebrates to comprehensively track the evolution of reasoning abilities, in particular, and cognition, in general.

Sex differences in visuospatial cognition- a female advantage in jigsaw puzzle solving.

Mentally visualizing objects, understanding relationships between two- or three- dimensional objects, and manipulating objects in space are some examples of visuospatial abilities. Numerous studies have shown that male participants outperform female participants in visuospatial tasks, particularly in mental rotation. One exception is solving jigsaw puzzles. Performance by seven- to eight-year-old girls was found to be superior to that of boys of the same age (Kocijan et al. 2017). No study, however, has confirmed this finding in an adult population, where sex differences are often detectable. Seventy-nine young adult participants were given four different jigsaw puzzles and the Shepard and Metzler mental rotation test (MRT) with two main goals: First, to investigate possible sex differences in jigsaw puzzle solving, and second, to explore a potential relationship between mental rotation and jigsaw puzzle solving. We hypothesized that female participants would outperform males in the jigsaw puzzles but males would outperform females in the MRT. The findings confirmed this hypothesis. Notably, the male performance in jigsaw puzzle solving was attributed to their sex and mediated by their higher MRT scores. These results yielded two key insights. First, they indicate a dissociation between these two visuospatial abilities, jigsaw puzzle solving and mental rotation; and second, female and male participants capitalize on their distinct cognitive strengths when solving visuospatial tasks.

Dynamic modulation of the processing of unpredicted technical errors by the posterior cingulate and the default mode network.

The pervasive use of information technologies (IT) has tremendously benefited our daily lives. However, unpredicted technical breakdowns and errors can lead to the experience of stress, which has been termed technostress. It remains poorly understood how people dynamically respond to unpredicted system runtime errors occurring while interacting with the IT systems on a behavioral and neuronal level. To elucidate the mechanisms underlying such processes, we conducted a functional magnetic resonance imaging (fMRI) study in which 15 young adults solved arithmetic problems of three difficulty levels (easy, medium and hard) while two types of system runtime errors (problem errors and feedback errors) occurred in an unexpected manner. The problem error condition consisted of apparently defective displays of the arithmetic problem and the feedback error condition involved erroneous feedback. We found that the problem errors positively influenced participants' problem-solving performance at the high difficulty level (i.e., hard tasks) at the initial stage of the session, while feedback errors disturbed their performance. These dynamic behavioral changes are mainly associated with brain activation changes in the posterior cingulate and the default mode network, including the posterior cingulate cortex, the mPFC, the retrosplenial cortex and the parahippocampal gyrus. Our study illustrates the regulatory role of the posterior cingulate in coping with unpredicted errors as well as with dynamic changes in the environment.

Intervention effects on low performing preschoolers' early mathematical skills: Adding fundamental motor skill practice as a supporting method.

BACKGROUND: This study examined the effects of (1) combined early numeracy and fundamental motor skills (MovEN), (2) early numeracy, and (3) fundamental motor skills intervention programs on children's early mathematical and fundamental motor skills, and how individual background variables affect the effectiveness of these interventions. PROCEDURE: Together 50 preschoolers participated in the interventions (16 × 45 min sessions). Children's early numeracy, mathematical problem-solving, and fundamental motor skills were measured once before and twice after the interventions. MAIN FINDINGS: The results showed that the MovEN and early numeracy -interventions were effective in improving children's early numeracy, and mathematical problem-solving. Whereas the MovEN and fundamental motor skills interventions improved children's fundamental motor skills. From individual factors, only updating ability predicted the intervention's effectiveness over and above prior performance. CONCLUSION: The results suggest that children's early mathematical and fundamental motor skills can be supported effectively at the same time with the MovEN -intervention.

Unpacking the challenges and predictors of elementary-middle school students' use of the distributive property.

The distributive property plays a pivotal role in advancing students' understanding of multiplication, enabling the decomposition of problems and the acquisition of new facts. However, this property of multiplication is difficult for students to understand. We used two unique data sets to explore middle school students' use of the distributive property. Study 1 involved data from 1:1 structured interviews of students (N = 24) discussing worked examples and solving associated practice problems. We examined whether or not students used the distributive property to solve the problems and whether or not interviewers followed the recommended distributive property prompts or defaulted to more conventional methods. Despite exposure to worked examples using the distributive property and a protocol calling for attention to it, students and interviewers favored methods like PEMDAS (parentheses, exponents, multiplication, division, addition, subtraction) or long multiplication. Study 2 used a data set with middle school students' (N = 131) item-level responses on Kirkland's (2022; doctoral dissertation, University of Notre Dame) Brief Assessment of Mature Number Sense along with several related measures of domain-general and domain-specific skills. We extracted problems involving the distributive property for analysis. Surprisingly, there was no evidence that students' use of the distributive property improved from sixth grade to eighth grade. However, both grade-level mathematics achievement and cognitive reflection uniquely predicted the correct use of the distributive property. Results suggest that middle school students who exhibit stronger reflective thinking tend to perform better on distributive property problems. Findings highlight cognitive reflection as a potentially important construct involved in the understanding and use of the distributive property.