Search

Assessing preservice' higher order thinking skills (HOTS) in science and mathematics is essential. Teachers' HOTS ability is closely related to their ability to create HOTS-type science and mathematics problems. Among various types of HOTS, one is Bloomian HOTS. To facilitate the preservice teacher to create problems in those subjects, an Android app called EduAssess was developed as a Bloomian HOTS test for junior high school preservice teachers. This study aims to validate the problems in the EduAssess app through content validity. Content validity was analyzed using Aiken's V formula and expanded Gregory formula. EduAssess comprised three test sets for science and mathematics, each comprising 9 items. The instrument validated by three experts in each subject. The study results demonstrate that EduAssess, for both mathematics and science, has achieved content validity. Expert judgments confirmed the validity of EduAssess items, with Aiken's V index ranging from 0.67 to 1.00, meanwhile expanded Gregory index ranging from 0.78-1.00. The results showed that EduAssess includes analysis, evaluation, and creation. The findings highlight that the application instrument in facilitating pre-service teachers by measuring their ability to analyze, evaluate and create HOTS problems in science and mathematics subjects was proven valid and ready for data collection.

Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large language models (LLMs), we expect feedback as part of learning systems to transform, especially for the context of programming. In the past, it was challenging to automate feedback for learners of programming. LLMs may create new possibilities to provide richer, and more individual feedback than ever before. Objectives: This article aims to generate specific types of feedback for introductory programming tasks using LLMs. We revisit existing feedback taxonomies to capture the specifics of the generated feedback, such as randomness, uncertainty and degrees of variation. Methods: We iteratively designed prompts for the generation of specific feedback types (as part of existing feedback taxonomies) in response to authentic student programs. We then evaluated the generated output and determined to what extent it reflected certain feedback types. Results and Conclusion: This study provides a better understanding of different feedback dimensions and characteristics. The results have implications for future feedback research with regard to, for example, feedback effects and learners' informational needs. It further provides a basis for the development of new tools and learning systems for novice programmers including feedback generated by AI.

Although satisfaction with academic experience in the context of higher education has been an area of research for nearly 40 years, it is still unclear how pedagogical practices in the development of thinking skills are related to students' satisfaction. This study aims to investigate the relationships between students' satisfaction and the levels of thinking skills aligned with Bloom's revised taxonomy (BRT) taking into account students' characteristics. Relying on survey data (14 341 undergraduate students from five US universities), this study shows that when students are engaged in thinking skills higher on cognitive hierarchy of BRT, they are more likely to feel satisfied. Whereas engaging students in low thinking skills activities does not increase satisfaction with their academic experience. This study contributes to better understanding of how course design can be associated with student satisfaction and how instructors can implement the principles of BRT in their courses.

Several educational mapping techniques include mind mapping, concept mapping, knowledge mapping and competence mapping. This research used pedagogically informed competence maps featuring subject matter and learner capabilities. Mytelemap, a prototype tool, helps learners structure and visualise competence maps and provides study links based on map nodes. An experiment compared learning gains using Mytelemap with the general-purpose tool MindMeister across four web technology topics (HTML, CSS, CSS box model, WordPress) and two levels of Merrill's cognitive taxonomy (recall, use/apply). Results showed significantly higher learning gains with Mytelemap across all topics and taxonomic levels. Learners felt positively about competence mapping and preferred Mytelemap. In contrast, MindMeister showed only modest to negligible learning gains, highlighting the value of Mytelemap's link generation based on node keywords.

Purpose: For speech-language pathologists (SLPs) working in schools, outcome measurement is an important element of practice, enabling us to evaluate the efficacy of our service provision and guiding future decision making, funding, and resource allocation. When selecting outcomes to measure, it is helpful to consider both the level at which change may be occurring and the extent or impact of that change. The primary aim of this review was to identify the outcomes measured in intervention studies for school-aged children with speech, language, and communication difficulties (SLCD) using the International Classification of Functioning, Disability and Health to classify the outcomes. A second aim was to identify tools used in research studies to measure the outcomes. Method: A systematic search of five databases was undertaken to identify papers reporting outcomes for school students who had received intervention targeting SLCD. Articles written in English and published between January 2000 and August 2021 were included. The Taxonomy for Categorizing Outcome Measures for SLCD was created to enable a review of outcomes and measurement tools. Results: There were 125 papers included in the final review. Most papers (n = 109, 87.2%) reported on studies that included outcome measures that captured changes at Body Function level, while approximately half captured Activity-level change. Only 24 (19.2%) explored changes at Participation level. Conclusions: Change at the Body Function or Activity levels does not always reflect change at the Participation level. Measuring outcomes at the Participation level enables SLPs to determine the real-world impact of the adjustments they have recommended or the intervention they have provided. However, in order to measure outcomes at the Participation level, we need the tools for capturing those changes for school-aged students with SLCD.

Unlike other technologies that augment human physical skills and abilities, artificial intelligence (AI) technologies interact with human thinking skills nurtured through various educational processes. Hence, advances in these technologies challenge the education sector to reimagine the suitable intellectual formation of students in the AI age. It is observed that as soon as AI tools acquire certain cognitive skills, humans tend to delegate those skills to such tools, risking redundancy in their personal and professional lives. Therefore, anticipating an ever-increasing involvement of AI tools in various cognitive processes, educational systems must equip students with both AI-collaborative and AI-complementary thinking skills, making them resilient to the advancements of AI technologies. Furthermore, it demands that educators continually redefine the spectrum of thinking skills required for and imparted to students in the AI age. This article aims to develop a comprehensive taxonomy of educational objectives for AI-natives by reimagining thinking skills relevant in the AI age. It is intended to help educational policymakers worldwide reimagine the appropriate set of thinking skills relevant for students in the AI age. Additionally, the article provides important insights to restructure contemporary educational practices to meet the requirements of the holistic formation of the AI-natives.

This study based on cognitive and social semiotic theories investigates whether the influence of specific features of instructional representation from adolescent textbook images could last until adulthood in certain cultures. Two cultural groups, Indonesian (n = 61) and Taiwanese (n = 60) college students, were recruited from a public Taiwanese university. Reading an essay about how the biological five kingdoms were classified served as the foundation for student-generated drawings. Semi-structured interviews and verbal data were used to track the origin of influences in their drawings. The initial result of coding drawings revealed that most of the drawing structures were shared between groups while only the design of Evolution, revealing sequential taxa in the evolution history, was Taiwanese-specific. Further statistic testing indicated that only participants' nationality was a significant factor in determining the drawing structure while pedagogical content knowledge is not. A comparison of these results indicated that most Taiwanese representations agreed with that of the non-hierarchical design used in their prior textbook while the Indonesian representations agreed with the hierarchical design of their textbook. The results suggest that there are several competing factors interfering with the decision about image design. Suggestions for teacher education and further study are addressed.

This study aims to describe preservice mathematics teacher knowledge of higher order thinking skills in terms of definition, Bloom's taxonomy level, curriculum, learning, and evaluation. This research is quantitative research with a survey method. and sample consisted of 248 preservice mathematics teachers in semesters VI-VIII of the Department of Mathematics Education, Nusa Cendana University, Timor University, and Wira Wacana Sumba University. The instrument used was a questionnaire about high order thinking skill (HOTS) which consisted of 105 statements. Data analysis used Likert's summeted rating, one sample test, Mann Whitney, Kruskall-Wallis tests, multiple linear regression test, and multivariate analyisis of variance (MANOVA) test. The results showed that the knowledge level of preservice mathematics teacher was in the good category. Based on gender differences, there was no significant difference in the average knowledge of preservice mathematics teacherabout HOTS, there was a significant difference in the average knowledge of preservice mathematics teacher about HOTS which is significant based on differences in academic ability and gender differences do not significantly affect knowledge about HOTS levels in Bloom's taxonomy, curriculum, and pedagogy while academic knowledge has a significant effect on HOTS knowledge of preservice teachers in almost all aspects except for pedagogy.

Adaptive online learning can be realized through the evaluation of the learning process. Monitoring and supervising learners' cognitive levels and adjusting learning strategies can increasingly improve the quality of online learning. This analysis is made possible by real-time measurement of learners' cognitive levels during the online learning process. However, most of the currently used techniques for evaluating cognitive levels rely on labour-intensive and time-consuming manual coding. In this study, we explore the machine learning (ML) algorithms and taxonomy of Bloom's cognitive levels to explore features that affect learner's cognitive level in online assessments and the ability to automatically predict learner's cognitive level and thus, come up with a recommendation or pedagogical intervention to improve learner's acquisition. The analysis of 15,182 learners' assessments of a specific learning concept affirms the effectiveness of our approach. We attain an accuracy of 82.21% using ML algorithms. These results are very encouraging and have implications for how automated cognitive-level analysis tools for online learning will be developed in the future.

Strategic competence, the ability to use communication strategies (CS) to overcome challenges and enhance communication effectiveness, is crucial in language learning. However, the coverage of these strategies as well as target models to teach them remain scarce in current instructional materials. This paper represents the first attempt to examine the application of ChatGPT in providing target models of CSs and facilitate L2 learners' strategic competence. ChatGPT-4 was used to generate transcripts of monologues and dialogues around a description task following two types of prompts: with and without a taxonomy of communication strategies (structured and unstructured prompts). Preliminary findings suggest Chat-GPT's considerable potential in modeling communication strategies. Across the two prompting conditions, the chatbot was able to present a wide range of CSs, including achievement, self-monitoring, timegaining, and interactive strategies. The highest CS content was found in the structured-prompt dialogue which utilized 9 out of 10 CS sub-types, a more diverse range than typically covered in textbooks, with approximation, circumlocution, and time gaining being most frequently used. In terms of linguistic presentation, the AI-generated transcripts demonstrated appropriate use of CSs, though their linguistic realizations were limited in range. The article concludes with implications for leveraging Chat-GPT to contextualize communication strategies, considerations for prompt engineering, strategy training to proficiency levels, and AI-teacher collaboration.

Despite the common title of "coach," definitions of high-quality coaching vary tremendously across models and programs. Yet few studies make comparisons between different models to understand what is most helpful, for whom, and under what circumstances. As a result, practitioners are left with many options and little evidence-based direction. This is exacerbated by the literature's focus on more abstract features of coaching practice (e.g., building trust), leaving practitioners to figure out what concrete discourse strategies support these goals. This article begins to address these challenges by introducing a taxonomy of coaching "moves," parsing the concrete details of coach discourse. While the taxonomy is informed by the literature, it highlights conceptual possibilities rather than providing a list of empirically grounded or "evidence-based" strategies. In doing so, this taxonomy may serve as a common language to guide future work exploring how coach discourse shapes teacher development, synthesizing across studies, and supporting coach practice.

Fink's Taxonomy of Significant Learning (FTSL) is an instructional strategy that provides an effective framework for (re)designing course learning experiences to achieve student-centered learning goals. Originally developed for in-person courses, little research exists around its application to effectively design distance learning (DL) courses. This study aims to evaluate if the online learning community can also utilize FTSL as a strategy for supporting online learners toward achieving significant learning goals. To address this aim, faculty applied FTSL during the redesign of an asynchronous DL general education course for undergraduates, which involved redesigning course learning objectives and goals, then realigning and revising the course assessments and learning activities. A deductive, manifest content analysis was conducted to measure achievement of course learning goals across all nine written course assessments (n = 40 student participants). Then, learning frequencies were quantified for each category of significant learning. Study findings indicate most student participants engaged in learning experiences related to five of the six categories within Fink's taxonomy several times throughout the semester, with higher frequencies of learning in categories for application, followed by the human dimension and foundational knowledge, then caring and integration. In conclusion, study findings support that applying FTSL during the course (re)design process also supports online learners toward achieving significant learning goals, with course assessments that include analysis, aesthetic learning, and self-reflection as useful exercises for achieving said goals. Future research can build on this study by evaluating if online learners who achieve significant learning goals also experience long-lasting change relevant to the learner's life (i.e., engage in a significant learning experience). [Note: The page range (378-401) shown on the PDF is incorrect. The correct page range is 360-383.]

The article moves away from the traditional architectural basic design education methods and approaches it within the framework of the discipline of educational sciences and learning models. The multi-layered education structure transforms into a new learning field under the guidance of Bloom's Revised Taxonomy, which proposes a course schedule for the architectural basic design studio. Taxonomy allowed us to discover the reflections and effectiveness of the interdisciplinary structure of architecture and design in the educational process and to be instrumentalized and used in the context of basic design education. The course schedule proposal presents a flexible schedule outline with the example of an interdisciplinary studio schedule. The trial created within the scope of this study can be appropriately organized for different Ecoles, schools, and values. The paper is significant for its interdisciplinary nature and develops a new discourse using Bloom's Revised Taxonomy. Using Bloom's Revised Taxonomy as a method in the studio has led to a paradigm shift in methodology.

The present study analyses the impoliteness of criticism over social status and distance, incorporating the concept of "levels of imposition." Criticism as a fundamental speech act is commonly used by people in the modern era, either in the digital world or the real world. It usually contains impoliteness if it embodies negative behavior, conveying criticism. This study belonged to an interlanguage pragmatics study and used forty participants from English language learners having Javanese backgrounds. It also applied the role play technique to take data to be analyzed using mixed method analysis. The data showed that the criticizer performed various impoliteness strategies in criticism, considering familiar and unfamiliar relationships in different social status levels. They mainly performed bald-on-record impoliteness and adhered to other strategies such as negative, positive, and mock politeness. Besides that, delivering criticism in high intonation was also perceived as a part of impoliteness. Therefore, it suggested conducting another research concerning paralinguistics and impoliteness in various communication contexts.

Learners' acquisition of pragmatic competence in additional languages has received mounting attention since the 1990s. However, although studies on general learning strategies have proliferated since Oxford's (1990) influential inventory was published, studies on pragmatic-specific learning strategies contributing to the acquisition of this competence are rare. To fill this research gap, the current study purported to inquire into the main pragmatic learning strategies used by English language learners across gender and language learning experience. To collect the data, 145 learners were interviewed. These participants' answers were audio-taped and transcribed. These extracted strategies were organized into six groupings of memory-related, cognitive, metacognitive, compensatory, social, and affective pragmatic learning strategies based on Cohen's (2005, 2010) pragmatic-specific categorization and Oxford's (1990) general language learning strategy classification. The analysis showed that those learners with longer experience used more pragmatic learning strategies; nonetheless, gender did result in great differences in employing these strategies. This study presents a new categorization for pragmatic learning strategies, which can be used for more effective pragmatic learning strategy teaching and learning.

Virtual reality has emerged as an influential technology in the educational landscape, offering learners and teachers immersive and interactive experiences that enhance traditional teaching methods. However, despite the increasing importance of virtual reality in education, a systematic description and classification of virtual reality use cases in education is still lacking. This limits the understanding and comparability of virtual reality use cases and highlights the need for a structured approach. This study asks the research question: How can virtual reality educational use cases, identified in the literature, be described, and classified? To classify these use cases, this study develops a state-of-the-art taxonomy. The taxonomy was developed in a combination of a conceptual-to-empirical and empirical-to-conceptual approach. The first stage to develop the taxonomy was based on a conceptual-to-empirical approach. Here, the concepts of virtual reality, use case and education serve as meta-characteristics and theoretical structure. To further detail the dimensions and characteristics, a systematic literature review was conducted by following a PRISMA-guided search and selection process. Therefore, the scientific databases Science Direct, AISel and Springer Link were used to search for studies between 2018 and 2023, obtaining a sample of 39 publications. As the conceptual-to-empirical approach did not richly describe the analysed virtual reality use cases from the studies, additional dimensions and characteristics were identified inductively. Therefore, a second iteration was conducted relating to the empirical-to-conceptual approach. This process explored the practical aspects of virtual reality scenarios and added applicable and practical characteristics to the initial theoretical foundation. The result is a comprehensive taxonomy of virtual reality use cases in education that contributes significantly to existing knowledge and provides a solid foundation for future research. The final taxonomy includes 17 dimensions and 37 characteristics. These findings can support educators to understand the nature of virtual reality use cases, enabling them to describe and implement such use cases effectively within educational settings. [Note: The publication year (2023) shown in the citation on the PDF is incorrect. The correct publication year is 2024.]

Since the mid-90s, a growing concern has emerged regarding text comprehension from a multimodal perspective. In the Chilean educational context, multimodality has been highlighted in the official programs of the Ministry of Education. The present study examines one of the official Chilean ELT school textbooks, investigating whether its reading comprehension questions align with the country's interest in developing multimodal literacy. This analysis employs Unsworth et al.'s (2019) taxonomy for classifying question types to examine 17 while-reading sections, comprising 216 questions. The findings reveal a predominant focus on questions that can be answered by reading the written text without looking at the pictures as well as a lack of images in several reading passages. These results highlight the crucial role that teachers play in complementing the school textbooks, enabling students to develop multimodal literacy as well as the necessity for textbook designers to recognize the pivotal role of images in comprehending multimodal texts.

Over the years, a sweeping interest in translanguaging practices and corrective feedback (CF) in parallel has received momentum in instructed SLA research. Whereas previous CF studies focused on CF interactions and factors affecting L2 learning, this study examined how translanguaging intertwined with CF in Arabic as a Heritage Language learning in a sixth-grade class at a K-12 school in the USA. The research data resulted from twenty hours of class observations, interviews with the class teacher, and ten randomly selected participating students. The data were coded based on Ranta and Lyster's (2007) CF types and uptake moves taxonomy. The results showed that the teacher's translanguaging practices helped learners engage in pedagogical tasks and CF interactions, leading to effective Arabic language learning. The teacher provided five CF types--explicit correction, recast, metalinguistic feedback, elicitation, and multiple feedback. Metalinguistic feedback, recast, and multiple feedback accounted for 72% of CF, where recasts received the highest uptake and repair rates (95% and 87%, respectively), and the other types of CF also led to high uptake and repair moves. This study suggests that CF can be effective when teachers employ translanguaging during CF interactions, positively address learner errors, and motivate learners' in-class participation.

Biology education plays a vital role in nurturing the understanding of learners about the intricacy of life. Various efforts have emerged to strengthen learning biological concepts but there were still studies that showed that learners have low mastery in some aspects. To determine how well students understood various biological topics, including human physiology, Concept inventory tests (CIT) were used. The concept inventory test may be able to spot students' misconceptions and ultimately lead to improved comprehension. The crafted CIT developed with the aid of a table of specifications based on Bloom's taxonomy of cognitive domain was assessed according to its validity and reliability. In validation, content validity and item analysis were considered while reliability test was employed through Cronbach's alpha. Distractor analysis was also performed to determine possible source of misconception per item. The CIT was administered to 120 senior high school STEM students (50.8% from the private schools, 37.5% in regular public schools and 11.7% from public schools with special programs in science). The results displayed high content validity with a mean of 4.83 for content validity and an average Aiken's validity coefficient of 0.98. It also highlighted that the test is moderately difficult with the test difficulty of 0.58, as well as, discriminatory with a discriminating level of 0.46. After item classification, 63 items were retained (39 accepted, 24 for revisions) and Chronbach's alpha ([alpha]=0.74) indicated good internal consistency. The concept inventory test propounds to be a good classroom test science with minor items to be revised.

This paper reports the results of a qualitative action research study conducted with children from a private Colombian institution. This study aimed to analyze the learners' cognitive and knowledge outcomes measured according to the revised Bloom's taxonomy once content and language integrated learning was implemented. Data were gathered through an interview with the learners' parents, observation, and video recordings. Results give evidence that learners develop different processes simultaneously, classified by the mentioned taxonomy. This taxonomy is a helpful approach for English learners since it allows them to perform cognitive and knowledge processes without following rigid systematic learning. As a conclusion, this implementation with children allowed participants to develop cognitive processes with greater emphasis in levels 3 and 4 (apply and analyze), whereas level 2 (understand) was developed as part of the process. Meanwhile, the factual and conceptual knowledge dimensions were strengthened. Finally, procedural, and metacognitive knowledge is developed through the implementation itself.

In this study, it was aimed to develop an achievement test taking into account the subject acquisitions of the sound and properties unit in the sixth-grade science course. In the test development phase, firstly, literature review for the study was conducted. Then, 30 multiple choice questions in align with the subject acquisition in the 2018 science curriculum. This 30-question test was presented to opinion of three academicians and a science teacher for the validity of the test. Necessary adjustments were made in line with the opinions of the experts. Subsequently, the draft test, modified according to the experts' feedback, was applied to a total of 300 seventh grade students. After the analysis, the number of questions in the test was reduced to 27. As a result of item analysis, mean difficulty index value of the test was 0.41, and item discrimination index was 0.49. The reliability analysis for the developed test was found 0.92 by calculating the KR-20 reliability coefficient value. By considering, the validity and reliability analysis results, it was concluded that the final version of the developed test, grounded in Bloom's Taxonomy, is a valid and reliable test with different difficulty levels.

Numerous studies compared the effectiveness of various formats of video-based teaching, yet their focus has primarily been on relatively straightforward content, such as concepts and basic procedures. Research on the effectiveness of teaching complex content through different formats of videos remains limited. This study addresses this gap by conducting a well-controlled comparison between recorded video and narrated animation in the context of teaching physics problem-solving, a challenging content area with easily measurable difficulty levels. The study employed a controlled experimental design with a sample of 361 upper secondary school students who had been randomly assigned to seven classes within a selected secondary school by the school administrator. Data were collected using pre- and post-test assessments that measured students' problem-solving performance after video-based teaching. The results indicated that the effectiveness of recorded videos featuring the teacher's face was not significantly different from that of narrated animations that did not include the teacher's face, irrespective of the content's difficulty level. These findings provide valuable insights for educators in selecting appropriate teaching formats for teaching challenging content through video-based education. They contribute to our understanding of teaching strategies and have practical implications for educators seeking to optimise teaching approaches in similar contexts.

Involving students in the design of their educational experience is increasingly being understood by higher education institutions to enhance learning, to build a better culture, and to foster inclusivity, amongst a host of other benefits. Accordingly, institutions are trialling a range of students-as-partners practices. There is currently huge variation in the nature and scale of these practices. This paper charts the process of putting names to various characteristics of students-as-partners practices in order to consistently describe, and therefore compare and map, them. The taxonomy that results is of immediate utility, but adapting the taxonomy to a specific context is also recommended as a profitable exercise. The processes described in this paper are vital next steps in the development and widespread adoption of this transformational set of practices.

This research uses Bloom's taxonomy in English-language writing and speaking skills assessment rubrics. A descriptive qualitative research method was adopted, and data were collected through observations, interviews, and English major students' course grades. Five lecturers and 25 students participated in the research, and the findings revealed that applying Bloom's taxonomy in an assessment rubric focuses on cognitive assessment at the two lowest levels, namely knowledge and understanding. We also identified five benefits of applying Bloom's taxonomy, mainly motivating students and improving learning performance based on the criteria. Therefore, the assessments helped the lecturers and students achieve their teaching and learning goals. The findings presented here have implications for developing learning curricula, improving basic competencies, creating indicators for achieving semester learning plans, and achieving educational goals at local and international levels.

Classifying, naming, and identifying insects have been complicated topics among science teachers and students. This problem is due to the highly technical collection protocols, safekeeping procedures, the unavailability of appropriate learning resources, and the closure of school laboratories and facilities due to the COVID-19 pandemic. Using the remote learning setup, this study utilized Improvised Insect Traps (IITs) to provide an authentic learning experience in teaching and learning insect taxonomy at home. The study aimed to determine the effects of using IITs on students' self-efficacy beliefs and perceived levels of engagement. In this quasi-experimental study, 42 students designed and developed their improvised insect traps. Insect collection and classification were accomplished within four weeks. A 20-item validated survey questionnaire on self-efficacy and engagement levels was administered via Google Forms. Students' feedback was gathered using virtual focus group discussions and open-ended questions. Results revealed that IITs effectively improved students' self-efficacy beliefs (Z=0.033, p-value=0.022, g=0.68), while no improvement was noted in students' perceived levels of engagement (Z=0.143, p-value=0.188, g=0.07) in teaching and learning insect taxonomy. Moreover, students' feedback and responses were classified as Affordances or Constraints. Subthemes such as motivation, satisfaction, authentic learning, safety, and parental involvement were generated in the thematic analysis. Overall, this study found that the IITs activity is relevant in teaching insect taxonomy and delivering practical learning experiences among students in a distance learning modality.

A cohort of pre-service mathematics students was exposed to a teaching strategy based on retrieval practice and test-potentiated learning. The aim of the study was to determine how high and low prior topic knowledge study participants compare in terms of their procedural fluency and conceptual understanding after exposure to the teaching strategy. A pre-test and post-test repeated measures design was employed in the study to compare within groups. A revised taxonomy table based on Bloom's taxonomy was utilised to categorise test items. Findings indicate significant differences between pre-test and post-test scores within groups. Results from the independent samples t-test show a significant difference between the two groups. Outcomes confirm that the benefits of retrieval practice are greatest for unfamiliar content. Findings indicate that for low prior topic knowledge students, procedural fluency is enhanced and retained more than conceptual understanding whereas for the high prior topic knowledge students it was the reverse. The strategy was not as effective for improving conceptual understanding.

This paper presents a unified Arabic version of the English action verbs mentioned in Bloom's taxonomy (1956) that has been checked for validity and reliability by a panel of education experts. Methodologically, the Bloom's list of action verbs was first translated into Arabic by an expert professor of translation. Then, using a mixed-method approach the Arabic list was validated by three bilingual education experts working at universities in Bahrain, Qatar, and the United Arab Emirates. As part of the process, the paper established a single Bloom's taxonomy list of action verbs, based on the data provided by two reputable educational institutions that were cross-checked with a well-referenced textbook. A contextualized Arabic translation of the list was then produced and was subjected to rigorous checks by a panel of reviewers who were the education experts. The paper presents the challenges faced in translating the list into Arabic and the solutions we have adopted as well as the validity and reliability checks. The implication of this paper is in offering teacher preparation programs across the Arab world an Arabic Bloom's taxonomy list that can be used by in-service and pre-service teachers. Moreover, it contributes to teacher literacy in the correct use of Bloom's action verbs in the Arabic language.

Mathematical symbols, such as those embodying quantum concepts, are indispensable for conveying complex ideas and relationships in academic writing. However, some education researchers and students keep a distance from anything mathematical: algebraic equations, geometrical reasoning, or statistical symbols. How to lower the access threshold for this type of mathematical narrative and reveal the meanings of a range of quantum conceptions to modern educators thus becomes a real problem. Using the pendulum motion equation as a reference point, I argue in this article for the advantages of academic English or French writing genres that fuse a range of mathematical symbols of quantum concepts and conceptual change. Such writings help demonstrate how incorporating the idea of probability (a) refines the debate among conceptual, verbal, and mathematical academic writing; (b) allows new conceptions that draw on the insights from quantum cognition-supported theories; (c) helps explain students' understanding of mathematical symbols; and (d) offers a new taxonomy for categorizing academic writings.

Large introductory classes, with their expansive curriculum, demand assessment strategies that blend efficiency with reliability, prompting the consideration of multiple-choice (MC) tests as a viable option. Crafting a high-quality MC test, however, necessitates a meticulous process involving reflection on assessment format appropriateness, test blueprint design, and adherence to item-writing guidelines aligned with learning objectives and teaching strategies. This inherently time-consuming undertaking ideally requires a collaborative effort from a team of writers who possess expertise in both the subject domain and the specific course context -- an aspiration complicated by the multifaceted demands of higher education instruction. Given these challenges, educators often seek pragmatic solutions, including the adoption or adaptation of existing MC tests. However, the utility of these tests is ambiguous if the original test blueprint and the classification of questions are unknown. This paper introduces a structured four-step "reverse engineering" test blueprint process and proposes a systematic approach to identify test questions that align with the targeted learning objectives. One crucial step incorporates the Taxonomy Table (Anderson & Krathwohl, 2001) facilitating the classification of questions in the cognitive process dimension. As we delve into the intricacies of this analytical journey, we aim to provide a valuable resource for educators seeking to optimize the effectiveness and relevance of MC tests as a high-stakes assessment option.

Critical thinking, creativity, communication, teamwork, emotional intelligence, problem-solving, empathy, resilience, ambition, grit, and innovation (Heckman & Kautz, 2012). These skills, often referred to as 'soft' skills, are considered a requirement for employment and advancement for the 21st-century graduate (Carnevale & Smith, 2013). Within a Western Canadian School of Business, in an environment highly regarded for technical skill achievement in diploma and degree graduates, faculty set out to investigate the absence or inclusion of human skills in curriculum outcomes as an initial phase of investigation. There is an institutional presumption that human skill development is innately a part of the programs. The intention is that human skills (LeBusque, 2020) or power skills (PMI, 2022) naturally occur during course delivery, creating a commonality across foundational courses to reinforce the skill sets identified, developed, and refined as students complete their credentials. However, industry reports (Lapointe & Turner, 2020; RBC, 2019) and the authors' own institutional data collected from new graduates and employers indicated room for improvement in these skills. To gain a better understanding, the authors undertook an examination via document analysis of all common core courses that form the program foundation. Through the lens of dynamic skill theory (Mascolo, 2020), this evaluation involved 24 common courses, comprised of 1,442 course objectives, resulting in a range of 134 Bloom's Taxonomy verbs. In this paper, the authors begin the exploratory first phase of a broader comprehensive study with a focus on course foundations for learner development. Through this analysis, the authors present a draft framework to better understand and strengthen the learning foundations, to proceed with considerations for realignment and strategic scaffolding of both technical and human skills from entry through graduation.

Research confirms that critical thinking plays a fundamental role in decision making and problem solving, skills that are essential to function as successful adults in a complex world. Consequently, it has been a focus of educational research for decades. Faculty meetings and teacher training sessions repeatedly run sessions on ways that teachers can adapt their methodology to foster higher-level thinking. This article discusses the definition of critical thinking and the pivotal role that questioning can have in developing those skills. Out of the hundreds of questions teachers ask daily, few demand higher-level thinking. In fact, most ask for basic information or check for current learning rather than causing students to infer, analyze, evaluate, or demonstrate creativity. Further, the article includes a sampling of teaching techniques adapted from cooperative learning and other disciplines that have the potential to transform the world language classroom into a vibrant, learner-active space where students use critical thinking to solve problems.

The present study falls into the efforts to improve practices for addressing errors produced by learners in various situations involving the calculation of integrals. We attempt to clarify as precisely as possible the types of errors that secondary school students produce when using integrals in algebraic and graphical frames. Based on the synthesis of several works dealing with errors specific to integral calculus, we have been able to outline a typology of possible errors that can be produced by students in secondary school. We determine some subcategories for the three known categories of errors: conceptual, procedural, and technical. After administering a test to a random sample of secondary school students and conducting a principal component analysis, we were able to deduce that in the algebraic frame, certain conceptual and procedural subcategories dominate, with a notable advance for errors due to failure to recognize the integrand function. In the graphical frame, errors related to technical subcategories represent a major source of the erroneous productions of the students tested.

Vertebrate species knowledge is one of the predictors of pupils' understanding of biodiversity. This study will describe vertebrate species identification skills of pupils from the Czech Republic. Altogether, the research tool included 30 vertebrate species, out of which five were fish, three were amphibians, three were reptiles, nine were birds, and 10 were mammals. The research tool consisted of 22 pictures, three footprints, two silhouettes, and three sounds. In addition, we evaluated the influence of variable factors on vertebrate species knowledge, which the research tool also contained. The paper will describe the percentage success rate of vertebrate species knowledge of 1537 respondents. On average pupils could identify nearly 15 species. The results showed that differences in species knowledge were statistically significant mostly by pupils' expectations (self-efficacy) or their results and educational level. In general, younger students identified animals worse than students of higher levels of education. Moreover, significant differences were confirmed between the five classes of vertebrates. Mammals were the best-identified class, followed by amphibians and fish; reptiles and birds were the least correctly identified. While educational level played a significant role in identification skills, the results revealed that the pupils' hometown did not play a significant role.

The overarching goal of this impact project is to make mycology accessible to more agriscience educators and students. Lesson plans were prepared to link core competencies and science standards to the Wild-Foraged Mushroom certification. Incorporating mycology into the classroom has many benefits, including discussions on food safety and regulation, the role of ecology in agroecosystems, and taxonomic identification skills. Fungi also play many different roles in the ecosystem, including decomposers, mutualists, and parasites. Lesson plans in three topic areas were produced: mushroom identification and fungal ecology, mushroom growth and food safety, and mushrooms as a renewable resource. Examples of hands-on learning and connections to the Wild-Foraged Mushroom certification are provided. This certification is available in the state of Michigan; however, lessons could be adapted for use in other regions of the United States. Looking at taxonomy, ecology, food science, and economics through the lens of mycology is an engaging way to motivate students while potentially helping them earn a certification.

Learning design has become increasingly important in the context of expanding and dynamic digital learning environments. More traditional teaching approaches are no longer sufficient to engage learners in these changing learning environments. Teachers and aspiring learning designers therefore increasingly need learning design expertise, which takes time to develop. This paper responds to this challenge by outlining a fishbone digital learning design method, which is aligned with updated versions of Bloom's taxonomy for the digital world, as a scaffolded approach to developing basic learning design expertise. The study integrates three practical tools into one learning design method to ensure constructive alignment. The findings contribute to digital educational development and teacher professional development by proposing a practical and easy to adapt learning design method.

Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level representation, i.e., learning performance that sheds light on learners' knowledge and ability to apply skills after course learning in the education process. Emerging Artificial Intelligence (AI) predicts future learning performance in the higher education system. This research aims to implement an AI application using a supervised learning model to predict students' learning abilities, which are developed by the end of course study. The authors examine learners' performance skills using Bloom's classifiers. This study aims to develop more innovative ways to represent learners' knowledge level by implementing AI models in learning performance. This prediction model assists both teacher and learner in understanding learners' knowledge abilities, and this study can find out the current status of learners' knowledge.

Background: In response to the call for papers under the theme "What is in a name" proposed by the Scientific Child Speech Committee of the International Association of Communication Sciences and Disorders (IALP), the current paper discusses taxonomy and its relation to speech sound disorders (SSD) from a cross-linguistic perspective. Aims: This paper starts with a brief description of specific SSD frameworks and nomenclature. Methods & Procedures: The authors draw from international theoretical and clinical research which underscore the importance of taxonomy systems in SSD. Outcomes & Results: The current papers stresses the importance of the contribution to differential diagnosis and prognosis of children with protracted speech profiles on the bases of taxonomy profiles and systems for SSD. Conclusions & Implications: The advantages and shortcomings of taxonomy in SSD are also discussed from a cross-linguistic context. The language of focus includes the Greek dialectal variation of Cypriot-Greek.

In this article, Ingrid Andersson discusses the decolonial philosophy of Sylvia Wynter, with a special focus on addressing her concepts of the hybrid human and origin stories. Andersson shows how Wynter's philosophizing about the "being" of being human is premised on an entanglement of nature and culture that is on par with the posthuman understanding of the ontological inseparability of matter and discourse. She goes on to interrogate some productive tensions between Wynter's decolonial philosophy and posthumanism by pointing out how Wynter's hybrid human formulates an understanding of human nature that is different in itself and not solely in relation to other nonhuman entities. In the final part of the article, she proposes how we, with Wynter, can devise a pedagogical approach that seeks to counteract harmful taxonomizing practices.

We propose a simple computational model that describes potential mechanisms underlying the organization and development of the lexical-semantic system in 18-month-old infants. We focus on two independent aspects: (i) on potential mechanisms underlying the development of taxonomic and associative priming, and (ii) on potential mechanisms underlying the effect of Inter Stimulus Interval on these priming effects. Our model explains taxonomic priming between words by "semantic feature overlap," whereas associative priming between words is explained by Hebbian links between semantic representations derived from "co-occurrence relations" between words (or their referents). From a developmental perspective, any delay in the emergence of taxonomic priming compared to associative priming during infancy seems paradoxical since feature overlap "per se" need not be learned. We address this paradox in the model by showing that "feature overlap" itself is an emergent process. The model successfully replicates infant data related to Inter Stimulus Interval effects in priming experiments and makes testable predictions.

There is a need to conceptualize a multidimensional taxonomy for learner-AI interaction. This conceptual/perspective article shares recent work on AI learner education and further presents new conceptions for a multidimensional taxonomy for learner-AI interaction. A review of the literature is conducted (N = 11). Open coding is used to summarize an overview of work, challenges, and findings reported. The summarized work is then used to conceptualize considerations for a multidimensional taxonomy for learner-AI interaction. The contribution of this work is in identifying unforeseen limitations in characterizing human-AI interaction and presenting new conceptions for a multidimensional taxonomy for learner-AI interaction based on the synthesis of the reviewed literature. This work thus shares current findings and challenges reported by the literature and our conceptions. Four conceptions are introduced, namely the alignment between the learner and AI; diverse metrics for the learner, AI, and learner-AI interaction; feedback direction when summarizing interactions; and what works in human-AI interaction by using prior research. We find there to be challenges with the use of AI by humans. The more interaction time spent between humans and AI may not necessarily lead to enhanced learning and understanding. Humans may exploit and use AI in inappropriate ways such as plagiarism. This eminent threat begs the question to reconsider our evaluation methods in light of AI systems.

In this article we propose a taxonomy describing various types of literature review or theoretical/conceptual articles. We distinguish each article type based on how well they address the "summary" and "advocacy" arguments inherent in all secondary scholarship. Understanding this taxonomy of review/theory scholarship is critical because our field encompasses theory, research, and design, and thus needs to be expansive in our understanding of scholarship, including secondary research. Some scholars conduct comprehensive/systematic reviews that answer the summary question of "what we" know. Meanwhile, other scholars develop conceptual frameworks that guide our future design and research by answering the advocacy question of "what we should do." Many do not understand the differences between these different types of review scholarship, their roles, and the process and quality criteria for writing them. This limits our ability to teach students, review the variety of review and theory scholarship submitted to our journals, and propel our field forward. The taxonomy, scholarship process, and quality criteria presented in this article proposes a way forward in understanding the role of secondary scholarship in developing knowledge in our field.

An individual competence is one of the main human resources, which enables a person to operate in everyday life. A competence profile, formally captured and described as a structured model, may enable various operations, e.g., a more precise evaluation and closure of a training gap. Such application scenarios supported by information systems are particularly compelling for the era of digitalisation, although research on adequate models capturing competence profiles is still lacking; moreover, no research was revealed synthesizing models of competence, enabling operationalisation possibilities. To fulfil this gap, current research develops a classification of competence models in the form of taxonomy, derived from operational characteristics of competence constructs. Given conceptual fuzziness of the competence term and complex, interdisciplinary scope of the study, the research method follows integrative literature review principles: results of an extensive search conducted in three iterations were critically analysed and further synthesized in the form of taxonomy. This critical analysis was performed based on an overview of twenty-four competence models with a lens of working definitions of competence framework and model concepts. As a result, all three outcomes highlight the power of competence models: (1) the overview summarises models' development methods, operationalisation, and purposes in a specific application domain, while (2) working definitions and (3) the taxonomy aim at overcoming a conceptual ambiguity of competence concepts. In addition, the presented taxonomy may serve as a knowledge base or a decision support tool on competence model selection when it comes to development of a competence management tool.

Developing immersive learning systems is challenging due to their multidisciplinary nature, involving game design, pedagogical modelling, computer science, and the application domain. The diversity of technologies, practices, and interventions makes it hard to explore solutions systematically. A new methodology called Multimodal Immersive Learning Systems Design Methodology (MILSDeM) is introduced to address these challenges. It includes a unified taxonomy, key performance indicators, and an iterative development process to foster innovation and creativity while enabling reusability and organisational learning. This article further reports on applying design-based research to design and develop MILSDeM. It also discusses the application of MILSDeM through its implementation in a real-life project conducted by the research team, which included four initiatives and eight prototypes. Moreover, the article introduces a unified taxonomy and reports on the qualitative analysis conducted to assess its components by experts from different domains.

The adoption of large language models (LLMs) in education holds much promise. However, like many technological innovations before them, adoption and access can often be inequitable from the outset, creating more divides than they bridge. In this paper, we explore the magnitude of the country and language divide in the leading open-source and proprietary LLMs with respect to knowledge of K-12 taxonomies in a variety of countries and their performance on tagging problem content with the appropriate skill from a taxonomy, an important task for aligning open educational resources and tutoring content with state curricula. We also experiment with approaches to narrowing the performance divide by enhancing LLM skill tagging performance across four countries (the USA, Ireland, South Korea and India-Maharashtra) for more equitable outcomes. We observe considerable performance disparities not only with non-English languages but with English and non-US taxonomies. Our findings demonstrate that fine-tuning GPT-3.5 with a few labelled examples can improve its proficiency in tagging problems with relevant skills or standards, even for countries and languages that are underrepresented during training. Furthermore, the fine-tuning results show the potential viability of GPT as a multilingual skill classifier. Using both an open-source model, Llama2-13B, and a closed-source model, GPT-3.5, we also observe large disparities in tagging performance between the two and find that fine-tuning and skill information in the prompt improve both, but the closed-source model improves to a much greater extent. Our study contributes to the first empirical results on mitigating disparities across countries and languages with LLMs in an educational context.

In its original version, control-value theory describes and explains achievement emotions. More recently, the theory has been expanded to also explain epistemic, social, and existential emotions. In this article, I outline the development of the theory, from preliminary work in the 1980s to early versions of the theory and the recent generalized control-value theory. I provide summaries of the theory's evidence-based propositions on antecedents, outcomes, and regulation of emotions, including the fundamentally important role of control and value appraisals across different types of human emotions that are relevant to education (and beyond). The theory includes descriptive taxonomies of emotions as well as propositions explaining (a) the influence of individual factors, social environments, and socio-cultural contexts on emotions; (b) the effects of emotions on learning, performance, and health; (c) reciprocal causation linking emotions, outcomes, and antecedents; (d) ways to regulate emotions; and (e) strategies for intervention. Subsequently, I outline the relevance of the theory for educational practice, including individual and large-scale assessments of emotions; students', teachers', and parents' understanding of emotions; and change of educational practices. In conclusion, I discuss strengths of the theory, open questions, and future directions.

Despite decades of research efforts, data-based instruction (DBI) for students with intensive intervention needs are not being widely used in practice as anticipated, and many educators have difficulties in implementing it. This systematic review aimed to examine what kinds of implementation drivers and strategies have been used to support educators implementing DBI and what kinds of implementation outcomes researchers have measured. Eighteen studies were synthesized using the Implementation Drivers framework and Implementation Outcomes taxonomy and were quality appraised. We found that the majority of studies primarily used competency drivers to increase teachers' DBI expertise, while a limited number of studies focused on organizational and leadership drivers. Acceptability and fidelity were frequently assessed as implementation outcomes. We discussed the implications of the findings, including the need for researchers to incorporate implementation drivers and outcomes at diverse levels to best support educators' implementation of DBI, as well as the limitations of this review, such as the limited generalizability of the findings.

Despite problem posing's prominence in mathematics education research, its implementation in classrooms is limited. Therefore, teacher educators should incorporate problem posing tasks into preparation programs to help prospective teachers gain confidence in their abilities. One approach to teaching problem posing includes providing examples. The Common Core State Standards Initiative provides taxonomies with examples of one-step word problems for all four basic operations. Through this mixed-methods study, preservice teachers (N = 44) regularly identified and posed word problems within the addition and subtraction taxonomy. Before and after the intervention, the preservice teachers answered survey questions and posed problems to model given equations. The researchers analyzed the preservice teachers' abilities to pose logical word problems and to match given equations before and after instruction. They also quantitatively analyzed Likert-style survey responses on perceptions of posing the various types of word problems and integrated the results with a qualitative analysis of open-ended responses expanding on the same questions. Results showed participants' abilities to pose problems increased after the intervention. Additionally, participants felt problems with the unknown information at the beginning or middle were harder to pose than those with the unknown information at the end.