Levels Of Prior Knowledge Research Articles

Comprehension and Understanding of Gestational Diabetes Mellitus Among Pregnant Women Attending Primary Health Care Facilities in Jeddah, Saudi Arabia.

Background and objective Gestational diabetes mellitus (GDM) is a form of diabetes that develops during pregnancy and can negatively affect both the mother and the fetus. This study aimed to assess the knowledge and awareness of GDM among pregnant women in primary care centers. By enhancing their understanding of the risks and symptoms of GDM, we can potentially mitigate adverse outcomes. Methods A cross-sectional study was conducted in the National Guard's primary healthcare facilities in Jeddah, Saudi Arabia. The study employed a validated 12-item questionnaire to collect data from 489 participants. The questionnaire items covered the identification of risk factors, diagnostic approach, treatment options, and complications related to GDM, considering maternal and fetal health implications. Results The study participants had a mean age of 30.9 years. Among these participants, 53.6% demonstrated a thorough understanding of GDM, 35.2% had moderate knowledge scores, and 11.2% had low knowledge scores. Higher levels of awareness were strongly associated with higher levels of education, gravidity, and prior knowledge of GDM. Conclusion The study highlights the importance of early detection and management strategies for GDM during pregnancy to minimize its negative impacts. Thefindings suggest the need for individually tailored antenatal education programs by healthcare professionals that address the needs of different populations. This is particularly relevant for women with lower education levels and those who are pregnant for the first time or have no prior knowledge of GDM.

How to help students in their transition to middle school? Effectiveness of a school-based group mentoring program promoting students’ engagement, self-regulation, and goal setting

School transitions are labeled as challenging events in students’ academic paths likely to affect students’ development and engagement in school negatively. Grounded on extant research advocating the need to act preventively, school-based mentoring programs emerge as responses suited to provide students with developmental and instructional support during school transitions. Using a multivariate mixed-effects model for repeated measures quasi-experimental design, the present study assessed the effectiveness of a 12-session group mentoring program designed to promote fifth-grade students’ self-regulation, school engagement, and goal setting during their first school transition. Participants were 330 fifth graders in four schools randomly assigned to treatment or control conditions. Students’ self-reported measures were collected in four moments. Data were analyzed using a multivariate mixed-effects model for repeated measures analyses with two covariates (age and gender) and considering the students’ level of prior mathematics knowledge. Results indicated that participating in the group mentoring program led to improvements in all dependent variables. The effect size found was large considering all dependent variables simultaneously. However, when considered individually, the effect sizes were medium, small, or null, depending on the dependent variable. Lastly, and contrary to expectations, the effectiveness of our program was not influenced by students’ level of prior mathematics knowledge. The relevance of group mentoring programs in addressing students’ engagement and self-regulation needs is discussed. Future research and educational implications for designing mentoring programs are provided.

The effects of Multiple Representation Method and Prior Knowledge Level on Problem Solving Skills and Cognitive Load

In this study, the effect of multiple representation method and prior knowledge level in solving ill-structured problems was investigated. Quasi-experimental and 2x2 (multiple representation method x prior knowledge level) factorial designs were used in the study. The study group consists of 39 undergraduate students. The dependent variables of the study were determined as problem solving skills, cognitive load, and permanence. The independent variables were considered as multiple representation method (step-by-step, holistic) and prior knowledge levels (novice, expert). Prior knowledge level test, problem solving skills test and cognitive load scale developed to measure the variables were used as data collection tools within the scope of the study. The data was analysed with two-way analysis of variance and independent groups t-test as the data obtained from the data collection tools exhibited normal distribution. In the results that were significant in the analysis, Cohen (d) in the independent groups t-tests and eta-square (η2) in the two-way analysis of variance were also shown. As a result of the research, it is evident that the level of prior knowledge and the interaction (interaction effect) of the level of prior knowledge and the multiple representation method affect problem solving skills. In addition, it was concluded that the interaction of multiple representation method and prior knowledge level was statistically significant in terms of cognitive load variable. The findings supported the expertise reversal effect.

Loess landslides detection via a partially supervised learning and improved Mask-RCNN with multi-source remote sensing data

Loess landslides pose a severe threat of destruction, and detecting them is crucial for minimizing their impact on society. They typically consist of wind-deposited clay and silt, which makes them challenging to detect using conventional methods. Techniques like visual interpretation and field surveys are the most useful, yet these methods can be laborious, expensive, and require a certain level of prior knowledge. Furthermore, remote sensing approaches face the challenge of distinguishing between natural erosion and landslides. Recently, deep learning for landslide detection has the potential to speed up and improve detection accuracy. Nonetheless, deep learning models require large amounts of labeled data and the development of robust algorithms capable of extracting meaningful features from remote sensing data. In this article, a novel approach is introduced to improve the Mask Regional Convolutional Neural Network (Mask-RCNN) algorithm for accurately detecting landslides when the number of available segmentation mask samples is limited. Specifically, A novel loess landslides dataset is established using high-resolution remote sensing images in Gansu Province. In the context of partially supervised learning, a neural network branch containing a weight transfer function is developed to capture mask information from bounding boxes. Additionally, a mask-scoring network block is used to learn the quality of predicted instance masks. Our modified algorithm achieves an average precision improvement of 20.7% compared to the original Mask R-CNN algorithm in small landslide detection. The mask IoU threshold value of 0.5 is used to estimate the average accuracy higher than 0.75. The average precision of the segmentation mask is improved by 16.7% in test set. By proposing a solution that can achieve accurate landslide detection while using limited labeled samples, this study makes a valuable contribution to the application of deep learning in the domains of remote sensing and landslide detection.

Temporal Mapper: Transition networks in simulated and real neural dynamics.

Characterizing large-scale dynamic organization of the brain relies on both data-driven and mechanistic modeling, which demands a low versus high level of prior knowledge and assumptions about how constituents of the brain interact. However, the conceptual translation between the two is not straightforward. The present work aims to provide a bridge between data-driven and mechanistic modeling. We conceptualize brain dynamics as a complex landscape that is continuously modulated by internal and external changes. The modulation can induce transitions between one stable brain state (attractor) to another. Here, we provide a novel method-Temporal Mapper-built upon established tools from the field of topological data analysis to retrieve the network of attractor transitions from time series data alone. For theoretical validation, we use a biophysical network model to induce transitions in a controlled manner, which provides simulated time series equipped with a ground-truth attractor transition network. Our approach reconstructs the ground-truth transition network from simulated time series data better than existing time-varying approaches. For empirical relevance, we apply our approach to fMRI data gathered during a continuous multitask experiment. We found that occupancy of the high-degree nodes and cycles of the transition network was significantly associated with subjects' behavioral performance. Taken together, we provide an important first step toward integrating data-driven and mechanistic modeling of brain dynamics.

Where salience goes beyond authenticity

Abstract: This meta-analysis builds on and extends Chernikova, Heitzmann, Stadler, et al.’s (2020) meta-analysis on simulation-based learning in higher education by summarizing the findings of 214 empirical studies. The main focus of the current meta-analysis was to investigate the role of prior knowledge and design features, namely (1) the authenticity of simulated scenarios (as both functional correspondence with a real task and a physical resemblance of the environment) and (2) the salience of relevant information in moderating the effects of simulation-based learning on facilitating complex skills in higher education. The analysis identified that the salience of relevant information contributes significantly to explaining the variation in the effectiveness of simulation-based learning environments. We conclude that authenticity and salience can be assessed independently of each other, and both can be considered important design features in creating effective simulation-based learning environments to meet the needs of learners with different levels of prior knowledge.

Impacts of digital game-based flipped teaching approach on learning effectiveness of the students with different prior knowledge levels

ABSTRACT This study proposed a game-based flipped teaching approach and applied it to a HTML (HyperText Markup Language) course. We developed two versions of the pre-class content testing, one of which was game-based, using a “looking-through” game, and the other which was traditional, using a multiple-choice test. We conducted a teaching experiment of 9 weeks with 3 h per week. The valid sample was 39 students in the experimental group using the game-based version, and 32 in the control group using the traditional version. We hoped that the students’ learning effectiveness could be increased. However, adding the game may have different impacts on different human factors and different cognitive processes of Bloom’s taxonomy. To more precisely understand these problems, we divided the students into high and low prior knowledge, and divided learning effectiveness into the higher-level applying and analyzing aspects and the lower-level remembering and understanding aspects. The results showed that learners with low prior knowledge who originally lacked the foundational knowledge became interested in concentrating and then in the higher-level cognitive learning processes because of the experience of immersing themselves in the flow of the game. The learning effectiveness of their classroom participation significantly improved.

Factors Influencing Game-Based Learning in the Colombian Context: A Mixed Methods Study

Game-based learning (GBL) places high demand on educational resources and has been widely practiced in classrooms in many developed countries; however, few studies on GBL and its influencing factors have been conducted in developing countries. To address this research gap, a mixed-methods study was conducted in a state high school in the Amazon region of Colombia with 64 tenth-graders who were learning English as a foreign language to identify the factors that affect learners’ learning outcomes when serious games are applied to vocabulary learning, with a specific focus on learning engagement. This study drew on both quantitative and qualitative data collected from surveys, interviews, and pre- and post-tests. The results showed that engagement and prior knowledge can positively predict GBL outcomes, while contextual factors and family condition had an adverse impact on GBL outcomes (Adjusted R2 = 0.635, p < 0.01). The results also indicated that a male student with a higher level of prior knowledge would be more likely to achieve good grades in GBL. Based on the study results, several implications are proposed for incorporating serious games for vocabulary learning in less-developed regions. This study results provide important practical implications for high schools in developing countries to implementing GBL.

Exploring how children with reading difficulties respond to instructional supports in literacy games and the role of prior knowledge

AbstractDigital literacy games can be beneficial for children with reading difficulties as a supplement to classroom instruction and an important feature of these games are the instructional supports, such as feedback. To be effective, feedback needs to build on prior instruction and match a learner's level of prior knowledge. However, there is limited research around the relationship between prior knowledge, instruction and feedback in the context of learning games. This paper presents an empirical study exploring the influence of prior knowledge on response to feedback, in two conditions: with or without instruction. Thirty‐six primary children (age 8–11) with reading difficulties participated: each child was assessed for their prior knowledge of two suffix types—noun and adjective suffixes. They subsequently received additional instruction for one suffix type and then played two rounds of a literacy game—one round for each suffix type. Our analysis shows that prior knowledge predicted initial success rates and performance after a verbal hint differently, depending on whether instruction was provided. These results are discussed with regards to learning game feedback design and the impact on different types of knowledge involved in gameplay, as well as other game design elements that might support knowledge building during gameplay. Practitioner notesWhat is already known about this topic Instructional supports, such as elaborative feedback, are a key feature of learning games. To be effective, feedback needs to build on prior instruction and match a learner's level of prior knowledge. Prior knowledge is an important moderator to consider in the context of elaborative feedback. What this paper adds Providing additional instruction (eg, pre‐training) may act as a knowledge enhancer building on children's existing disciplinary expertise, whereas the inclusion of elaborative feedback (eg, a hint) could be seen as a knowledge equaliser enabling children regardless of their prior knowledge to use the pre‐training within their gameplay. Highlights the importance of children's preferred learning strategies within the design of pre‐training and feedback to ensure children are able to use the instructional support provided within the game. Possible implications for pre‐training and feedback design within literacy games, as well as highlighting areas for further research. Implications for practice and/or policy Pre‐training for literacy games should highlight key features of the learning content and explicitly make connections with the target learning objective as well as elaborative feedback. Pre‐training should be combined with different types of in‐game feedback for different types of learners (eg, level of prior knowledge) or depending on the type of knowledge that designers want to build (eg, metalinguistic vs. epilinguistic). Modality, content and timing of the feedback should be considered carefully to match the specific needs of the intended target audience and the interaction between them given the primary goal of the game.

A structural equation model to analyze the use of a new multi media platform for increasing awareness of cultural heritage

Dedicated multi media platforms have the potential to enhance experiences and increase people's awareness of cultural heritage. It is, however, not clear to what extent and by which functions these platforms accomplish this. Therefore, the aim of this research is to investigate the influence of functionalities offered by a well-designed multi-media web-platform on the awareness and experience of cultural heritage. The multi media platform used is focused on Strijp-S, an industrial cultural heritage in Eindhoven, the Netherlands. The platform was created as a prototype based on a study of users' preferences for contents and media types offered. To collect data, a sample of 302 respondents used the platform to explore and view Strijp-S. To test assumed relationships between different functionalities, awareness and experience in an integrated fashion, the data are analyzed using Structural Equation Modelling (SEM). The results show that information-collection funtionality plays a significant role in improving awareness of cultural heritage, whereas auxiliary functions are particularly helpful for enhancing experiences. The perceived helpfulness of these two sets of functions differ however between users depending on theitr level of prior knowledge. Policymakers and urban planners can use these results to create their own platform based on local heritage to increase the citizens' awareness of cultural heritage.

Prior knowledge as a moderator between signaling and learning performance in immersive virtual reality laboratories.

The purpose of this study is to investigate the effects of signaling and prior knowledge on the cognitive loads, motivations, and learning of college students in an immersive virtual reality (IVR) environment. This study applied a 2 (signaling vs. no signaling) by 2 (high vs. low prior knowledge levels) between-subjects factorial design. The results revealed that signaling directed the attention of students with low prior knowledge levels, effectively helped them select relevant information and reduced their cognitive loads, whereas signaling had no significant effect on the cognitive loads, intrinsic motivation, and learning performance of learners with high levels of prior knowledge. These results suggest that IVR environments for students with low prior knowledge levels should reduce cognitive load and improve learning, and signals in the form of text annotations and color changes are recommended for additional support. Students with high prior knowledge levels do not require additional signals to support learning; therefore, the IVR environment needs to be designed in such a way as to be tailored to the individual differences of students.

Computer-based multimedia testing: Effects of static and animated representational pictures and text modality

Static representational pictures (RPs) have been focused in research on the multimedia effect in testing and might be especially important in arithmetical word problems, which require a multi-stage mental processing to segment the task. To further highlight the task segments visually, dynamic visualizations could help. However, conventional animations might not apply to this context and the role of dynamic visualizations with temporal segmentations (i.e., animated RPs) is unexplored. This classroom experiment with 456 students investigated multimedia and modality effects in 24 mathematical word problems. Our 3 × 2 mixed design included three multimedia conditions (static RPs, animated RPs, and text-only) and two modality conditions (written text vs spoken text). We investigated effects on response correctness, metacognitive ratings, item-solving satisfaction and time on task. Both static and animated RPs increased response correctness, item-solving satisfaction, and metacognitive ratings compared to text-only. Time on task was affected in distinctive ways in both RP conditions and also varied depending on text modality. Spoken text barely increased response correctness in animated RP items but not at all in static RP items. Moderator analyses revealed that the effects of static and animated RPs on response correctness were dependent on the text modality but varied across school types and the level of mathematical prior knowledge. For students at non-academic-track schools or with low prior knowledge, static and animated RPs improved response correctness compared to text-only across both modalities. For students at academic-track schools or with high prior knowledge, mainly combinations of static or animated RPs with spoken text were effective.

Jokes in Italian as a foreign language: comprehension, funniness, and sharing

This paper analyses whether the comprehension of a joke in Italian as a foreign language is influenced by personal or task elements, whether comprehension influences the perception of funniness, and whether perceived funniness affects intention to share the jokes. A quantitative cross-sectional study was performed. Participants were all native Spanish speakers from Mexico who also read Italian as a foreign language. There were 61 participants, aged 19-64 years (Mage = 26.3; SD = 9.4), comprising 42 females and 19 males. Comprehension was measured using a multiple-choice test. Funniness was measured by a perception scale and sharing was measured by determining intention to share. The objectives were fourfold: to identify whether factors related to the test-taker (gender, occupation, and age) influenced comprehension; to investigate whether factors related to the test task (level of language, reading support, and prior knowledge) influenced comprehension; to explore if comprehension influenced the perception of funniness; and to determine whether funniness influenced the intention to share. To statistically evaluate these question, four generalized linear models were constructed (one corresponding to each objective). The results indicated that: (i) the test-taker’s occupation affects comprehension (p = 0.0499); (ii) the interaction of all of the test-task factors influences comprehension (p = 0.03087); (iii) comprehension affects funniness (p <0.001); and (iv) perceived funniness influences sharing (p <0.001). Finally, a discussion of these results is presented.

Perceived satisfaction of university students with the use of chatbots as a tool for self-regulated learning

Chatbots are a promising resource for giving students feedback and helping them deploy metacognitive strategies in their learning processes. In this study we worked with a sample of 57 university students, 42 undergraduate and 15 Master's degree students in Health Sciences. A mixed research methodology was applied. The quantitative study analysed the influence of the variables educational level (undergraduate vs. master's degree) and level of prior knowledge on the frequency of chatbot use (low vs. average), learning outcomes, and satisfaction with the chatbot's usefulness. In addition, we examined whether the frequency of chatbot use depended on students' metacognitive strategies. The qualitative study analysed the students' suggestions for improvement to the chatbot and the type of questions it used. The results indicated that the level of degree being studied influenced the frequency of chatbot use and learning outcomes, with Master's students exhibiting higher levels of both, but levels of prior knowledge only influenced learning outcomes. Significant differences were also found in students' perceived satisfaction with the use of the chatbot, with Master's students scoring higher, but not with respect to the level of prior knowledge. No conclusive results were found regarding frequency of chatbot use and the levels of students' metacognitive strategies. Further studies are needed to guide this research based on the students' suggestions for improvement.

Comparison of effectiveness of video-assisted learning and didactic lectures in learning physiology among 1st year MBBS students

Background: Video-assisted learning makes the learning environment effective and engaging for a wide range of learners with different levels of prior knowledge and interests. Aim and Objectives: The objectives of this study were to compare the effectiveness of video-assisted learning and didactic lectures as teaching methods among 1st year MBBS students and to evaluate the feedback regarding the teaching methods from students. Materials and methods: A quasi-experimental study was conducted among 100 1st year MBBS students. A pre-test in the form of MCQ was used to assess the knowledge regarding the topic. Students were divided into two groups based on their roll numbers. Group 1 attended video-assisted learning, while the group two students attended didactic lectures. At the end of session, post-test was provided to all students to assess the knowledge gained. Feedback was taken from students at the end of session. Statistical analysis was performed using two-way repeated measures mixed ANOVA to determine whether there is any difference in the average score before and after intervention as well as between the video assisted learning and traditional method. Mann–Whitney U-test was used for comparing the feedback score between two teaching methods. Results: There was statistically significant increase in the post test scores in both the group. Although both the teaching methods were equally effective, the score change was high in the video-assisted learning group but was not statistically significant (P = 0.907). Conclusion: Video-assisted learning is an effective learning method in physiology.

Does prior knowledge affect interaction dynamics and learning achievement in digital problem-based learning? A pilot study.

Previous research on problem-based learning (PBL) describes that videotaped observations develop meaningful insights into cognitive processes in tutorial groups. Analysis regarding the amount of prior knowledge on learning achievement has not been investigated in medical education so far, although both are key factors of PBL success. Thus, we intended to analyse videos of digital problem-based learning (dPBL) sessions, focusing on knowledge acquisition and interaction dynamics among groups with different levels of prior knowledge to reveal any distinctions. This study employed a pilot design by dividing 60 dental students into twelve subgroups with less or more prior knowledge, determined by a pre-semester multiple choice test (MCQ). The groups engaged in videotaped dPBL cases, which were examined regarding group interactions and tutor effectiveness. The learning achievement was assessed through a post-semester MCQ, an oral and practical exam. The video analysis showed that dPBL groups with less prior knowledge achieved significantly higher tutor effectiveness and group interaction utterances, but that the percentage of time in which utterances occurred was similar in both groups. Related to the MCQ results, the students with less prior knowledge learned four times more than those with profound previous abilities, but no significant difference was found in the results of the oral exam and practical exam. The interaction dynamics in dPBL depend on the group's amount of prior knowledge. Especially groups including participants with less prior knowledge seemed to benefit from dPBL in comparison to groups with more prior knowledge. The dPBL groups acquired knowledge in different ways during the courses but, finally, all students arrived at a similar level of knowledge.

Knowledge Level of Midwives before and after an Online Training Participation

Fetal growth restriction is a prevalent pregnancy issue linked to numerous unfavorable postnatal outcomes. Suboptimal uterine-placental perfusion and inadequate fetal feeding are the vital pathophysiologic causes. Midwives play a crucial role in informing pregnant women about vitamin D inadequacy. This paper aims to determine the difference between midwives' prior and post-webinar knowledge levels. It was a cross-sectional study of individuals who participated in a webinar on November 21, 2021. Subjects were selected using a total population sampling approach from all midwives who participated in the webinar and completed pre-and post-tests. The difference between knowledge levels was evaluated using the difference between the pre-test and post-test scores in the general category. There was an increase in the number of participants who successfully answered the five-question component, a decrease in the number of participants who correctly answered the two-question section, and no change in the number of subjects who correctly answered question number one. The average score on the post-test was higher (67.28) than the pre-test (63.10), while the median score was the same at both time points. After attending a webinar, there was an increase in the proportion of subjects with a high level of knowledge (11.4% to 24%) and a drop in the proportion of subjects with a poor level of knowledge (32.3% to 27.1%). In conclusion, there was an improvement in the knowledge level of midwives before and after the webinar participation.

Effectiveness of Instruction with Manipulative Materials on Fourth Graders’ Geometry Learning Achievement

The concepts of geometrical figures, shape, and size are essential for learning their features, relations, and proofs. In the geometry classroom, a good teacher is expected to use the objects related to geometrical shapes for the real concept and knowledge of the figures, and to improve the learning achievement of young learners. In this context, this study aimed to compare the learning achievements obtained from using and without using manipulative materials in teaching geometry, especially in grade four, and identify students' general attitudes and feelings towards the instruction with the demonstration of the concrete objects. For this purpose, the researcher employed the Basic Experimental and Post-test Only Control Group Design to form two groups, the Experimental Group and the Control Group, having a similar level of prior knowledge and competence in geometry. Each group consisted of 13 students studying in grade four at Kapiya Secondary School, Khairahani, Chitwan, Nepal. The same achievement test was conducted for both groups after a month's intervention. The t-test was used to draw the significant deviation between the achievements. The result showed that the mean achievement of the learners who were instructed through manipulative objects was better than the achievement of the learners instructed without using them. After the test, some students from the Experimental Group were chosen for the interview to uncover their perceptions before and after the intervention. It revealed that students enjoyed the class based on learning with the manipulation of concrete objects. The study guides the mathematics teachers teaching junior classes to involve the students in the manipulation of different types of materials in geometry activities for the real concept of geometry and enhancement of learning achievement.

Do Domain Knowledge and Retrieval Practice Predict Students' Study Order Decisions?

Learning complex concepts is necessary for student success, but it is often challenging. Learning such concepts can be influenced by students' study order choices during learning to switch to a new category (interleaved study order) or stay within the same category (blocked study order). Students often prefer stay decisions during learning and make relatively few switch decisions; however, an open question is whether students' switch decisions are related to their level of prior knowledge in the domain and the learning strategy they use (retrieval practice versus study). To examine these relationships, we recruited undergraduate students from an introductory geology course. Prior to the course modules on rock classification, students self-rated their knowledge, took a prior knowledge test, classified rock exemplars by completing study or retrieval practice trials, and made study order choices. Students then completed assignments and attended lectures in their geology course on igneous, sedimentary, and metamorphic rocks. Next, students self-rated their knowledge, took a new prior knowledge test, completed study or retrieval practice trials, made study order decisions, took final classification tests, and self-reported beliefs about study order choices. Even though students' knowledge increased after course modules on rock identification, and most students believed that domain knowledge impacts study decisions, prior knowledge did not predict students' switch decisions. In contrast, students who completed retrieval practice trials made substantially more switch decisions (i.e., interleaved study) than did students who completed study trials.

Internal combustion engine test plan execution order optimization using Travelling Salesman Problem heuristics approach

For a given internal combustion (IC) engine stationary test plan, significant time savings during its realization could be achieved if the sequence of test points execution is adequately determined. The criterion for stabilizing the engine operating point is determined by the magnitude of the change in the most inert parameter, and in the general case, it is the temperature of the engine exhaust gases. A certain level of prior knowledge about the examined object is necessary to conduct such an analysis. If there are no results from previous tests, simulation models, or experiences, the Slow Dynamic Slope (SDS) tests are a great way to quickly gather the necessary information. The task of finding the optimal sequence for a stationary engine testing plan can be set as Travelling Salesman Problem (TSP). This paper will present the application of one of the heuristic methods for solving the TSP on the example of testing the IC engine, which is a very complex dynamic system. Following this model, it is possible to optimize the stationary test plan for any other dynamic system. The basic idea is to find such a sequence of stationary operating points, during the realization of which a minor deviation of the engine exhaust gas temperature is obtained, resulting in the operating point's shortest stabilization time.