Levels Of Cognitive Complexity Research Articles

An Investigation into the Utility of Large Language Models in Geotechnical Education and Problem Solving

The study explores the capabilities of large language models (LLMs), particularly GPT-4, in understanding and solving geotechnical problems, a specialised area that has not been extensively examined in previous research. Employing a question bank obtained from a commonly used textbook in geotechnical engineering, the research assesses GPT-4’s performance across various topics and cognitive complexity levels, utilising different prompting strategies like zero-shot learning, chain-of-thought (CoT) prompting, and custom instructional prompting. The study reveals that while GPT-4 demonstrates significant potential in addressing fundamental geotechnical concepts and problems, its effectiveness varies with specific topics, the complexity of the task, and the prompting strategies employed. The paper categorises errors encountered by GPT-4 into conceptual, grounding, calculation, and model inherent deficiencies related to the interpretation of visual information. Custom instructional prompts, specifically tailored to address GPT-4’s shortcomings, significantly enhance its performance. The study reveals that GPT-4 achieved an overall problem-solving accuracy of 67% with custom instructional prompting, significantly higher than the 28.9% with zero-shot learning and 34% with CoT. However, the study underscores the importance of human oversight in interpreting and verifying GPT-4’s outputs, especially in complex, higher-order cognitive tasks. The findings contribute to understanding the potential and limitations of current LLMs in specialised educational fields, providing insights for educators and researchers in integrating AI tools like GPT-4 into their teaching and problem-solving approaches. The study advocates for a balanced integration of AI in education to enrich educational delivery and experience while emphasising the indispensable role of human expertise alongside technological advancements.

Mix with the crowd? Craft‐based campaigns and the value of distinctiveness in campaign success

AbstractResearch SummaryDistinctiveness is an essential element of crafts. Building on optimal distinctiveness theory, we examine the relationship between craft‐based ventures, distinctiveness, and crowdfunding performance. Using a sample of 10,915 craft campaigns and 429,290 non‐craft campaigns, we find that craft‐based campaigns have higher distinctiveness but realize lower success through distinctiveness. Additionally, craft‐based campaigns with a higher risk index have lower distinctiveness, those with higher strategy breadth have higher distinctiveness, and those with lower cognitive complexity have higher distinctiveness. The findings have implications for crafts‐based entrepreneurs in leveraging distinctiveness and the value of lowering perceptions of distinctiveness through elements of strategic entrepreneurship—strategy breadth and cognitive complexity.Managerial SummaryOur study aids craft‐based entrepreneurs in presenting their ventures in crowdfunding contexts. We find that increasing the distinctiveness of craft‐based ventures results in lower crowdfunding campaign performance. Additionally, our results indicate that craft‐based campaigns that have higher risk have lower levels of distinctiveness. Conversely, we find that craft‐based campaigns with higher levels of strategic breadth and lower levels of cognitive complexity exhibit higher levels of distinctiveness. These findings have important implications regarding best practices related to how craft‐based entrepreneurs can best present their ventures within crowdfunding contexts. Specifically, our results indicate that craft‐based ventures can realize better crowdfunding performance via lower levels of distinctiveness within their campaigns.

To Compare the Efficiency of ChatGPT and Bard in Medical Education: An Analysis of MCQ-Based Learning and Assessment

Objective: This study aimed to compare the efficacy of ChatGPT and Google Bard as virtual tutors in supporting students across various levels of cognition in MCQ-based assessments in the field of Internal Medicine. Methods: This cross-sectional study was conducted in the Department of Internal Medicine in col- laboration with the Department of postgraduate medical education from June 2023 to October 2023. A comprehensive collection of multiple-choice questions (MCQs) covering various aspects of Internal Medicine was compiled by the research team’s consensus. The items were systematically organized into chapters and further categorized based on cognitive complexity levels (C1, C2, and C3). The cho- sen MCQs were entered into separate sessions of both ChatGPT and Google Bard. The responses from each Artificial Intelligence platform were then compared with the corresponding answers in the designated MCQs book. Recorded responses were classified as accurate, inaccurate, or partially ac- curate. Results: The ChatGPT exhibited an overall success rate of 64%, providing 199 correct responses out of 307 queries, of which 10 were partially correct. By contrast, Google Bard achieved an overall suc- cess rate of 58.95 %, yielding 181 correct responses out of 307 queries, where 16 were partially cor- rect. When stratified by cognitive complexity levels, ChatGPT demonstrated proficiency in solving C2 MCQs at a rate of 80%, whereas the performance rates for the C1 and C3 categories were 69% and 54%, respectively. In contrast, Google Bard displayed a 33% success rate in solving C2 MCQs while achieving success rates of 95% and 53% in the C1 and C3 categories, respectively. Conclusion: The findings of this study suggest that ChatGPT is a more advantageous tool for stu- dents and medical educators than Google Bard. These discerned advantages underscore the poten- tial of ChatGPT to enhance the educational experience within the medical domain.

Sustainability and Food Systems Concepts in Dietetic Training Standards in Speaking Spanish Countries

Introduction: Global calls for action to support sustainable development through food systems and nutrition provide context to examine to what degree nutrition and dietetics professionals are equipped for this challenge. The purpose of this research is to investigate content related to sustainable food systems in training standards from Spanish-speaking countries and examine what level of knowledge is required. Methods: Researchers conducted a content analysis of documents informing nutrition and dietetics training standards for content related to sustainable food systems, including dimensions of these complex topics. Relevant content was then analyzed according to the level of cognitive complexity per Bloom's Revised Taxonomy. Results: Of 21 eligible countries, documents describing competencies, standards or codes of ethics were found for six, four of which included relevant standards: Colombia, Mexico, Paraguay, and Peru. Overall, there was minimal comprehensive inclusion of sustainable food systems, but partial inclusion of one or more important sustainability dimensions. These were required at a mix of levels of cognitive complexity. Conclusions: This research adds to a small body of evidence documenting the state of readiness of nutrition and dietetics professionals to contribute to sustainable development. It highlights a moderate level of readiness in four Spanish-speaking countries, and opportunities for increased emphasis on comprehensive sustainability-informed education and training standards, which can help prepare practitioners for effective practice. Funding: MITACS Global Research Internship.

The cognitive neuroscience of self-awareness: Current framework, clinical implications, and future research directions.

Self-awareness, the ability to take oneself as the object of awareness, has been an enigma for our species, with different answers to this question being provided by religion, philosophy, and, more recently, science. The current review aims to discuss the neurocognitive mechanisms underlying self-awareness. The multidimensional nature of self-awareness will be explored, suggesting how it can be thought of as an emergent property observed in different cognitive complexity levels, within a predictive coding approach. A presentation of alterations of self-awareness in neuropsychiatric conditions will ground a discussion on alternative frameworks to understand this phenomenon, in health and psychopathology, with future research directions being indicated to fill current gaps in the literature. This article is categorized under: Philosophy > Consciousness Psychology > Brain Function and Dysfunction Neuroscience > Cognition.

Cognitive complexity measures for educational texts: Empirical validation of linguistic parameters

The article presents a study conducted within the framework of discourse complexology - an integral scientific domain that has united linguists, cognitive scientists, psychologists and programmers dealing with the problems of discourse complexity. The issue of cognitive complexity of texts is one of the central issues in discourse complexology. The paper presents the results of the study aimed to identify and empirically validate a list of educational texts’ complexity predictors. The study aims to identify discriminant linguistic parameters sufficient to assess cognitive complexity of educational texts. We view text cognitive complexity as a construct, based on the amount of presented information and the success of reader-text interactions. The idea behind the research is that text cognitive complexity notably increases across middle and high schools. The research dataset comprises eight biology textbooks with the total size of 219,319 tokens. Metrics of text linguistic features were estimated with the help of automatic analyzer RuLingva (rulingva.kpfu.ru). Linguistic and statistical analysis confirmed the hypothesis that text syntactic and lexical parameters are discriminative enough to classify different levels of cognitive complexity of educational texts used in middle and high schools. Text parameters that manifest variance in cognitive complexity include lexical diversity (TTR); local argument overlap; abstractness index; number of polysyllabic words, Flesch-Kincaid Grade Level; number of nouns and number of adjectives per sentence. Empirical evidence indicates that the proposed approach outperforms existing methods of text complexity assessment. The research results can be implemented in the system of scientific and educational content expertise for Russian school textbooks. They can also be of some use in the development of educational resources and further research in the field of text complexity.

ANALISIS TINGKAT KOGNITIF SOAL UJIAN SEKOLAH PADA MATA PELAJARAN PENDIDIKAN AGAMA ISLAM BERDASARKAN TAKSONOMI BLOOM REVISI 2001

This study aims to analyze the cognitive level of school exam questions on Islamic Religious Education subjects based on Bloom's Revised Taxonomy. Bloom's Revised Taxonomy is used as an assessment framework to describe the level of cognitive complexity requested by each exam question. The research method used was content analysis of Islamic Religious Education question banks from several schools covering primary and secondary education levels. The results of the analysis show that most of the Islamic Religious Education exam questions still concentrate on lower cognitive levels such as remembering and understanding. Higher cognitive levels such as applying, analyzing, evaluating and creating are rarely found in these questions. This indicates a tendency to use questions that tend to ask students to remember and understand religious concepts, rather than encouraging critical and analytical thinking skills

Method for Stress Detection in Industrial Assemblers Using Smartwatch Sensors

Goal: The purpose of this study is to present a method to quantitatively identify the levels of stress of employees during work using the technology of smart watches with sensors measuring vital signs and, from this data, deepen the discussion on the relationships between the levels of physical and cognitive complexity of the activities and their influence on the stress resulting from these works. 
 
 Theoretical reference: Use of literature through research on similar methods already applied in immersive training, dissertations, articles, and national standards. For this purpose, the Systematic Bibliographic Review (SBR) was used, which is “a scientific method for searching and analyzing articles in a given area of ​​science”. 
 
 Method: To achieve the objectives proposed in this work, a methodology with ten steps was developed. Four different workstations of an optical connector assembly company were selected to assess the stress levels of assemblers, using smart watch sensors, during their work activities. The workstations were evaluated for their physical load, through ergonomic analysis and for their cognitive load, through mental load classification. All data were statistically correlated. 
 
 Results and conclusion: Based on the statistical analysis of the data, it can be seen that the higher the level of complexity, the higher the average levels of stress presented. There is a direct influence on the level of stress and activities with greater complexity and related to physical (ergonomic) demands. The level of demand for carrying out activities, motivated by skills, rules and knowledge, mainly because they are related to decision-making, is related to the stress levels of employees, and can thus directly affect their mental health.
 
 Research implications: Through the results presented, we realized that reducing the demands of decision and reasoning during the activities requested at work, the company will be able to promote a reduction of the possible levels of stress of its employees, if this action does not impact on the reduction of their motivation for work. 
 
 Originality/Value: The method presented in this article differs from the others by comparing the different physical and mental demands with the stress levels measured with the use of smart watches during the activities of assembly line workers. It can be used to evaluate the effectiveness of an activity alternation approach, such as rotation, which can have a positive impact not only to minimize physical overloads but also to reduce levels of mental stress at work.

Paying Attention in Class: Using In-Class Quizzes to Incentivize Student Attention

Background Methods are needed to incentivize student attention to class material. Objective The purpose of this study was to examine the effects of in-class quizzing to incentivize student attention to class material to boost exam performance. Method A randomized, alternating treatments design embedded in an introductory psychology class compared learning benefits of two types of quiz-based engagement activities, mastery quizzes, and concepts checks, as compared to a no-engagement activity control. Results Students performed significantly better on exam content linked to classes with quiz-based engagement activities. Learning benefits of engagement activities extended across levels of cognitive complexity indexed to Bloom levels, although were stronger for low-level items. The effects of engagement activities were also stronger for content directly discussed in class. There were no significant differences in learning outcomes between the two engagement activities. Conclusion Students performed better on exam content linked to class sessions with quiz-based engagement activities that incentivized attention to class material compared to those that did not. Teaching Implications Using in-class quizzes as attentional cues offers instructors a means of incentivizing student attention to class material with minimal disruption of class time and lecture flow, while also improving exam scores.

Neural Indicators of Visual Andauditory Recognition of Imitative Words on Different De-Iconization Stages.

The research aims to reveal neural indicators of recognition for iconic words and the possible cross-modal multisensory integration behind this process. The goals of this research are twofold: (1) to register event-related potentials (ERP) in the brain in the process of visual and auditory recognition of Russian imitative words on different de-iconization stages; and (2) to establish whether differences in the brain activity arise while processing visual and auditory stimuli of different nature. Sound imitative (onomatopoeic, mimetic, and ideophonic) words are words with iconic correlation between form and meaning (iconicity being a relationship of resemblance). Russian adult participants (n = 110) were presented with 15 stimuli both visually and auditorily. The stimuli material was equally distributed into three groups according to the criterion of (historical) iconicity loss: five explicit sound imitative (SI) words, five implicit SI words and five non-SI words. It was established that there was no statistically significant difference between visually presented explicit or implicit SI words and non-SI words respectively. However, statistically significant differences were registered for auditorily presented explicit SI words in contrast to implicit SI words in the N400 ERP component, as well as implicit SI words in contrast to non-SI words in the P300 ERP component. We thoroughly analyzed the integrative brain activity in response to explicit IS words and compared it to that in response to implicit SI and non-SI words presented auditorily. The data yielded by this analysis showed the N400 ERP component was more prominent during the recognition process of the explicit SI words received from the central channels (specifically Cz). We assume that these results indicate a specific brain response associated with directed attention in the process of performing cognitive decision making tasks regarding explicit and implicit SI words presented auditorily. This may reflect a higher level of cognitive complexity in identifying this type of stimuli considering the experimental task challenges that may involve cross-modal integration process.

Formal language hierarchy reflects different levels of cognitive complexity.

Formal language hierarchy describes levels of increasing syntactic complexity (adjacent dependencies, nonadjacent nested, nonadjacent crossed) of which the transcription into a hierarchy of cognitive complexity remains under debate. The cognitive foundations of formal language hierarchy have been contradicted by two types of evidence: First, adjacent dependencies are not easier to learn compared to nonadjacent; second, crossed nonadjacent dependencies may be easier than nested. However, studies providing these findings may have engaged confounds: Repetition monitoring strategies may have accounted for participants' high performance in nonadjacent dependencies, and linguistic experience may have accounted for the advantage of crossed dependencies. We conducted two artificial grammar learning experiments where we addressed these confounds by manipulating reliance on repetition monitoring and by testing participants inexperienced with crossed dependencies. Results showed relevant differences in learning adjacent versus nonadjacent dependencies and advantages of nested over crossed, suggesting that formal language hierarchy may indeed translate into a hierarchy of cognitive complexity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

EduQG: A Multi-Format Multiple-Choice Dataset for the Educational Domain

Natural language processing technology has made significant progress in recent years, fuelled by increasingly powerful general language models. This has also inspired a sizeable body of work targeted specifically towards the educational domain, where the creation of questions (both for assessment and practice) is a laborious/expensive effort. Thus, automatic Question-Generation (QG) solutions have been proposed and studied. Yet, according to a recent survey of the educational QG community’s progress, a common baseline dataset unifying multiple domains and question forms (e.g., multiple choice vs. fill-the-gap), including readily available baseline models to compare against, is largely missing. This is the gap we aim to fill with this paper. In particular, we introduce a high-quality dataset in the educational domain, containing over 3,000 entries, comprising (i) multiple-choice questions, (ii) the corresponding answers (including distractors), and (iii) associated passages from the course material used as sources for the questions. Each question is phrased in two forms, normal and cloze (i.e., fill-the-gap), and correct answers are linked to source documents with sentence-level annotations. Thus, our versatile dataset can be used for both question and distractor generation, as well as to explore new challenges such as question format conversion. Furthermore, 903 questions are accompanied by their cognitive complexity level as per Bloom’s taxonomy. All questions have been generated by educational experts rather than crowd workers to ensure they are maintaining educational and learning standards. Our analysis and experiments suggest distinguishable differences between our dataset and commonly used ones for question generation for educational purposes. We believe this new dataset can serve as a valuable resource for research and evaluation in the educational domain. The dataset and baselines are made available to support further research in question generation for education (https://github.com/hadif ar/question-generation).

Factors of cognitive complexity of test questions in psychophysiological studies

The paper presents the results of a study of the functional state evaluations of the brain during auditory perception. The subjects listened 60 questions with different linguistic characteristics, taken from polygraph database templates, and answered to them. This characteristics: is the number of different types of words, the percentage of words from different parts of speech, the number of negations, the presence of forms of personal pronouns and their place in the question, the number of letters, the percentage of vowels, the position of intonational stress. As psychological characteristics that affect the functional state of the brain, the following were measured: verbal intelligence according to the R.Amthauer’s test, personal and situational anxiety according to the Spielberger — Khanin test. To measure the functional state of the brain, a 19-channel EEG was recorded in the 10–20% system. The functional state of the brain was assessed by calculating the fractal dimension of the EEG using the method. The sample consisted of students and employees of a number of educational institutions in St Petersburg, 9 men and 8 women aged 19 to 59 years. An analysis of the experimental data made it possible to confirm the hypothesis about the influence of the measured questionnaire characteristics, the linguistic characteristics of the questions, and the psychological characteristics of the subjects on the fractal dimension of the EEG. EEG analysis in various leads revealed two EEG “complexity” factors related to the frontal and occipital areas of the brain. A regression model was obtained for assessing the cognitive complexity of a particular test question, which is reflected in the complexity of the EEG curve of the subject perceiving this question. The resulting model allows you to select questions for psychophysiological examination that have the required level of cognitive complexity. The results of the work testify to the importance of such an indicator as the fractal dimension of the EEG for studying the functional state of the brain and its dependence both on the personal and biological characteristics of a person, and on the emotional state and complexity of the information received by the analyzers.

Sustainable food systems and diets in dietetic training standards: an international content analysis.

Low professional confidence and perceived competence create tangible barriers to integrating sustainable food systems (SFS) and diets into dietetic practice. One opportunity to facilitate more systemic integration into dietetic education and training is to include these concepts in professional standards. To better understand the barrier of low professional confidence and perceived competence for engagement with SFS-related practice, the purpose of this research was to investigate dietetic training standards for SFS content and to highlight opportunities for growth within the profession. Questions posed by this research are: (1) how, if at all, are SFS and diets articulated in dietetic training standards, and (2) to what level of cognitive complexity? A content analysis of dietetic training standards documents was conducted between 15 April and 15 September 2021. Search terms included 'sustain*' or 'sustainable', 'food systems' and/or 'diets'. Extracted data with applicable SFS content were analysed for level of cognitive complexity requirements. Of 47 National Dietetics Associations, researchers obtained 23 dietetic training standards documents, of which 16 included SFS-related content. The majority of documents used broad descriptors of the concepts, with little granularity and at a lower level of cognitive complexity. Adoption of more robust frameworks for sustainability with specific learning outcomes that can be adapted to regional contexts would strengthen higher education curricula and thus the profession's ability to contribute more meaningfully to SFSs and diets.

Facilitating supervisee cognitive development with the counselor cognitions questionnaire

ABSTRACT Cognitive development is a key area for supervisor emphasis, as supervisees with higher levels of cognitive complexity are able to formulate a thorough, balanced, multicultural understanding of their clients. Yet, there are few supervisory interventions that are designed to facilitate cognitive growth. Herein, we offer one such supervisory intervention using the Counselor Cognitions Questionnaire (CCQ). The CCQ is a specific yet repeatable intervention that captures an efficient snapshot of supervisee cognitions, triggers supervisee self-reflection, and offers supervisors relevant fodder for catalyzing supervisee cognitive growth.

Knowledge Acquisition and Social Support in Online Health Communities: Analysis of an Online Ovarian Cancer Community.

BackgroundPatients and caregivers widely use online health communities (OHCs) to acquire knowledge from peers. Questions posed in OHCs reflect participants’ learning objectives and differ in their level of cognitive complexity. However, little is known about the topics and levels of participants’ learning objectives and the corresponding support they receive from members of OHCs.ObjectiveThis study aimed to investigate the knowledge acquisition of patients and caregivers in an OHC. Specifically, we investigated the distribution and topics of posts with learning objectives at different cognitive complexity levels, the type and amount of social support provided to meet users’ learning objectives at different cognitive complexity levels, and the influence of social support on the change in learning objectives.MethodsWe collected 10 years of discussion threads from one of the most active ovarian cancer (OvCa) OHCs. A mixed methods approach was used, including qualitative content analysis and quantitative statistical analysis. Initial posts with questions were manually classified into 1 of the 3 learning objectives with increasing cognitive complexity levels, from low to high, based on the Anderson and Krathwohl taxonomy: understand, analyze, and evaluate. Manual content analysis and automatic classification models were used to identify the types of social support in the comments, including emotional support and 5 types of informational support: advice, referral, act, personal experience, and opinion.ResultsThe original data set contained 909 initial posts and 14,816 comments, and the final data set for the analysis contained 560 posts with questions and 3998 comments. Our results showed that patients with OvCa and their caregivers mainly used OHCs to acquire knowledge for low- to medium-level learning objectives. Of the questions, 82.3% (461/560) were either understand- or analyze-level questions, in which users were seeking to learn basic facts and medical concepts or draw connections among different situations and conditions. Only 17.7% (99/560) of the questions were at the evaluate level, in which users asked other OHC members to help them make decisions or judgments. Notably, OvCa treatment was the most popular topic of interest among all the questions, regardless of the level of learning objectives. Regarding the social support received for different levels of learning objectives, significant differences were found in the advice (F2437.84=9.69; P<.001), opinion (F2418.18=11.56; P<.001), and emotional support (F2395.88=3.24; P=.01), as determined by one-way ANOVA, whereby questions at the evaluate level were more likely to receive advice, opinion, and emotional support than questions at the lower levels. Additionally, receiving social support tends to drive users to increase the cognitive complexity of the learning objective in the next post.ConclusionsOur study establishes that OHCs are promising resources for acquiring knowledge of OvCa. Our findings have implications for designing better OHCs that serve the growing OvCa community.

Measuring cognitive potential based on the performance of tasks of various levels of complexity

Purpose of work. The article is devoted to the topic of measuring the cognitive potential of a person on the basis of the obtained experimental data in order to identify its potential capabilities, as well as to monitor their dynamics, for example, to diagnose recovery after an illness. This goal is divided in the study into two tasks, namely, to assess the cognitive potential, it is necessary to develop two algorithms: 1. Assessment of the level of cognitive complexity of tasks. 2. Systems of levels of cognitive potential for an individual. Methods. The basis of the methods is a set of experimental, including specially developed author’s, techniques, as well as mathematical methods for processing data and calculating the entered specific parameters to formalize the cognitive potential. Results. On the basis of these methods, methods (and specific formulas) are proposed for calculating the cognitive potential of an individual using experimental data and tasks of various levels of complexity. Conclusion. Within the framework of this study, a methodology for determining the value of cognitive potential was created on the basis of the theory of information images / representations, as well as a specially developed web-toolkit for objectifying cognitive skills (including the so-called softskills). This value can be useful, both in studies related to changes in cognitive abilities as a result of the influence of various internal and external factors (for example, learning, diseases, injuries, etc.), diagnostic goals (for example, with the aim of determining the speed recovery after a disease that affects cognitive activity, such as a stroke or SARS-CoV-2), and in the formation of requirements for certain work positions that significantly depend on the cognitive abilities of the individual.

From Simple to Complex: The Relationship Between Educational Leaders’ Cognitive Complexity and Leadership-Style Profiles

ABSTRACT This innovative study examines the relations between principals’ cognitive complexity (CC) levels and their leadership-style profiles. Participants were 341 principals and 3,209 teachers in Israel. Results indicated four leadership-style profiles: transformational; mixed – including transformational and transactional; transactional; and passive-avoidant. School principals were further found to juggle their perspectives from simple to complex, resulting in passive-avoidant to transactional, to transformational and to mixed leadership profiles. The mixed leadership-style profile (transactional and transformational) was characterized by high CC, and construed social behavior in a multidimensional way; passive-avoidant leadership was characterized by simple thinking (low CC).

Task sequencing and L2 writing development: Exploring the SSARC model of pedagogic task sequencing

To test the predictive power of the SSARC (stabilize, simplify, automatize, reconstruct, and complexify) model of pedagogic task sequencing in second language (L2) writing development, the present study explores the performance of written decision-making tasks with varied levels of cognitive complexity in a simple-to-complex sequence in comparison to complex-to-simple and individual task performance sequences over time. The participants, 100 advanced-mid learners of English as a second language (ESL), who were divided into three groups completed writing tasks either (1) in a simple-to-complex sequence, (2) in a complex-to-simple sequence, or (3) at one level of complexity (i.e. simple, medium, or complex task versions). Their written production was analysed for syntactic complexity, accuracy, lexical complexity, and fluency (CALF). Quantitative analyses found that the simple-to-complex group produced more syntactically complex and accurate essays over time than the complex-to-simple group, although neither group’s progression was linear. When the two sequencing conditions were compared to the individual task performance condition, the results showed more improvement in CALF in both sequencing groups than in the individual performance group over time, with more and steadier growth in the simple-to-complex condition. These findings support the SSARC model and expand current understandings of the relationship between cognitive task complexity and L2 writing development under different task sequencing conditions, with implications for L2 writing pedagogy.

Guy-Guessing Democracy: Gender and Item Non-Response Bias in Evaluations of Democratic Institutions

ABSTRACT Research on democratic attitudes has recently turned to examine citizens’ views about the performance of specific democratic institutions in their country. Drawing on data from the European Social Survey (ESS6) and the Bright Line Watch Project (BLW) in the United States, this article argues that such evaluative questions carry high levels of cognitive complexity that lead to gender gaps in item response rates. We then show that those gender gaps are present at every level of political knowledge and tend to be wider the less respondents know about the political system. Since women also tend to be more critical of democratic institutions, these results indicate that item non-response biases can make researchers underestimate overall levels of dissatisfaction with democracy, as well as overlook specific groups that may be particularly dissatisfied with the performance of certain parts of the democratic system.