Prior Knowledge Of Students Research Articles

The ability of seventh-grade disabilities students in solving number operation problems

This study aims to determine the ability of seventh-grade disabilities students (mental retardation) in solving number operation problems including addition, subtraction, multiplication, and division of natural numbers at SLB Bhakti Kencana I Berbah. The research method used is descriptive research to see the abilities and activities of students in solving number operation problems given by a researcher. The instruments of this study are a video to see students’ processes, test questions to see students’ abilities, and interviews with a teacher to encourage the student prior knowledge. The results of this study indicate that students still have difficulties in calculating the operation of natural numbers and forget how to calculate number operation according to what the teacher learns. In addition, the teacher mentioned that difficult to teach the concept of number operation.

Prediction of Student Final Exam Performance in an Introductory Programming Course: Development and Validation of the Use of a Support Vector Machine-Regression Model

This paper presents a Support Vector Machine predictive model to determine if prior programming knowledge and completion of in-class and take home formative assessment tasks might be suitable predictors of examination performance. Student data from the academic years 2012 - 2016 for an introductory programming course was captured via ViLLE e-learning tool for analysis. The results revealed that student prior programming knowledge and assessment scores captured in a predictive model, is a good fit of the data. However, while overall success of the model is significant, predictions on identifying at-risk students is neither high nor low and that persuaded us to include two more research questions. However, our preliminary post analysis on these test results show that on average students who secured less than 70% in formative assessment scores with little or basic prior programming knowledge in programming may fail in the final programming exam and increase the prediction accuracy in identifying at-risk students from 46% to nearly 63%. Hence, these results provide immediate information for programming course instructors and students to enhance teaching and learning process.

Exploring the Relationship Between Attentional Capture and Prior Knowledge in a Science-Based Multi-user Virtual Environment: an Individual Growth Model Analysis

In this study, we investigate trends in the relationship between what students know and the types of data that capture their attention over time in a science-based multi-user virtual environment. Longitudinal analyses of the patterns of data collected by 143 middle school students (nested within 5 teachers) showed that student prior knowledge was marginally (p < .10) related to variation in the attentional value (visibility and location) of data they collected over time, explaining about 2% of said variation. By contrast, accounting for the clustering of students by teacher was statistically significantly (p < .05) related to variation in trends in attentional values and explained 36% of said variation.

A Study on the Relationship among Knowledge Acquisition Sources at the Teacher- and College-Level, Student Absorptive Capacity and Learning Outcomes: Using Student Prior Knowledge as a Moderator

A Study on the Relationship among Knowledge Acquisition Sources at the Teacher- and College-Level, Student Absorptive Capacity and Learning Outcomes: Using Student Prior Knowledge as a Moderator

Guided inquiry activity linking thermodynamic parameters of protein unfolding to structure using differential scanning fluorimetry data in the biophysical chemistry classroom.

Visualizations are useful tools for helping students to understand chemistry concepts at the particulate level. A classroom activity was developed based on learning theory and evidence-based practices, combining protein visualization with thermodynamic parameters from differential scanning fluorimetry (DSF) data analysis. Coding of student responses showed that many students were able to establish the desired connections among protein structure, thermodynamic parameters, and experimental data analysis, while a few did not recognize all the differences between the folded and unfolded forms of the protein. The activity elicits student prior knowledge through the pre-class activity, has the students examine the interactions within a protein molecule through the PyMOL activity, introduces DSF analysis using the learning cycle through the Guided Inquiry activity, and tests student learning through the post-class activity. Upon completing the activity, the majority of students successfully met the learning goals. © 2018 International Union of Biochemistry and Molecular Biology, 47(1):67-75, 2018.

Exploring the Mediation of Learning of Chemical Equilibrium to High-achieving Students in a Selected Senior Secondary School in Namibia

Chemical equilibrium is one of the most important yet difficult topics to teach. The purpose of this study was to examine how two science teachers experienced the mediation of and how they mediated learning of this topic, chemical equilibrium, to high-achieving students. Data were collected using semi-structured interviews, lesson observations and stimulated recall interviews. The five topic-specific pedagogical content knowledge (TSPCK) components, namely, teacher knowledge of student prior knowledge, curricular saliency, what is difficult to understand, representations and conceptual teaching strategies, were used as conceptual tools to analyse the data. The findings revealed that the two science teachers struggled to mediate learning of chemical equilibrium concepts to high-achieving students and therefore the approaches used to teach them should not necessarily be any different from those used for average-ability students. Similarly, the teacher’s role as a mediator of meaningful learning is equally important for high-achieving students. We thus recommend that there is a need for continuing professional development for science teachers focussing on the development of materials and strengthening of their TSPCK components.

Investigating Students’ Physico-mathematical Difficulties in Classical Mechanics and Designing an Instructional Model

The study investigated students’ physico-mathematical difficulties in classical mechanics and designed an instructional model. The three objectives that guided the study were namely: to identify physico-mathematical difficulties students have in classical mechanics, to explore the existing instructional models and design a suitable instructional model to address physico-mathematical difficulties in classical mechanics and to verify and evaluate the effectiveness of the designed instructional model. The study was undertaken with a purposive sample of 140 students and 10 instructors learning and teaching classical mechanics respectively from the Copperbelt University and Mukuba University on the Copperbelt Province of Zambia. A descriptive mixed method survey design approach was used. A pilot study was conducted, instruments adjusted and survey implemented, instructional model designed and evaluated for its effectiveness. Four achievement tests comprising physico-mathematical concepts, the questionnaire, interviews and focus group discussions were used to collect data. The Microsoft Excel package was used to generate tables and percentages. Qualitative data from interview and focus group discussions were analysed qualitatively by the MAXQDA (Max Qualitative Data Analysis) software. The results of the study revealed that students had physico-mathematical difficulties in classical mechanics bordering on the students’ inabilities to use vectors, graphs, functions and mathematization in classical mechanics. Furthermore, it was found that the strategy of teaching mathematical concepts before introducing concepts in classical mechanics was used at the two institutions. However, these physico-mathematical difficulties still persisted. Therefore, the study recommended that instructors in classical mechanics should have necessary background information about students before teaching them. Information includes the prior knowledge of students. The study also recommended that instructors use suitable learning methods or materials that would engage students or make abstract physico-mathematical concepts more observable.

Sequencing support for sense making and perceptual induction of connections among multiple visual representations.

Making connections among multiple visual representations is key to students’ learning. This article considers two learning processes involved in connection making: explicit sense making of connections and implicit perceptual induction of connections. Instructional interventions support these processes via different problem types: sense-making problems ask students to verbally explain connections, whereas perceptual-induction problems ask students to quickly categorize numerous representations. Prior research shows that sense-making and perceptual-induction problems enhance students’ learning of domain knowledge—but only if both problem types are combined. Thus, one must ask whether the ability to make sense of connections enhances students’ ability to perceptually induce connections, or vice versa, and, consequently, which problem type students should receive first. This article investigates these questions in the context of undergraduate chemistry. Three experiments with 691 students compare instructional sequences that provide sense-making problems first or perceptual-induction problems first. Effects are assessed on problem-solving performance during the intervention and on chemistry knowledge learning gains after the intervention. Causal path analyses test whether working on sense-making problems first enhances (or impedes) students’ learning from subsequent perceptual-induction problems and vice versa. Results show that sequence interacts with prior chemistry knowledge: High prior-knowledge students show higher learning gains if they receive sense-making problems first. Low-prior-knowledge students show higher learning gains if they receive perceptual-induction problems first. Causal path analyses suggest that sense-making problems enhance students’ learning from subsequent perceptual-induction problems more so than the other way around. However, costs of switching between problem types interfere with low-prior-knowledge students’ ability to take advantage of this effect. (PsycINFO Database Record (c) 2018 APA, all rights reserved)

The Influence of Inquiry-Based Science Issues Learning on Practical Skills of Junior High School Students in Environmental Pollution Topic

Inquiry-based science issues approach facilitates the development of scientific skills through research activities on surrounding science issues. The purpose of this research was to understand the influence of Inquiry-based science issues on practical skills of Junior High School students. This research employed quasi-experimental research method, equipped with pre-test, post-test non-equivalent control group design. The sample of sixty junior high school students in Yogyakarta was picked for this study. The instruments used were observation sheets on practical skills, practical skills test, and instructional learning sheets. The data collected were analyzed using N-Gain, percentage, and Analysis of Covariate (ANCOVA) at 0.05 significance level. The result revealed that Inquiry Science Issues was more effective in fostering students’ practical skills than the scientific approach. There was a significant effect of treatment on students’ practical skills while no interaction between approach and prior knowledge of students. Moreover, the data of practical skills through the observation sheets in the experimental class had higher percentage compared to the control class, 80.36%, and 70.61% respectively.

The influences of self-regulated learning support and prior knowledge on improving learning performance

Self-regulated learning (SRL) is helpful to students. On the other hand, prior knowledge has great effects on students' self-regulation and learning performance. To this end, this study aimed to examine how high prior knowledge students (HPKs) and low prior knowledge students (LPKs) behaved differently when interacting with a SRL environment. To achieve this aim, we proposed a self-regulated learning support system (SRLSS) for a mathematical course. The results showed that the gap of learning performance between the HPKs and LPKs was removed after a long-term learning process. Moreover, the LPKs and HPKs behaved similarly in the forethought and self-reflection phases but some behavior differences were found in the performance phase, where the LPKs relied on the notes and sought support the dashboard and quiz records while the HPKs did not demonstrate such a tendency. Our results' theoretical and methodological implications and possible applications for further research are also discussed.

The influence of prior knowledge on experiment design guidance in a science inquiry context

ABSTRACTDesigning and conducting sound and informative experiments is an important aspect of inquiry learning. Students, however, often design experiments that do not allow them to reach conclusions. Considering the difficulties students experience with the process of designing experiments, additional guidance in the form of an Experiment Design Tool (EDT) was developed, together with reflection questions. In this study, 147 pre-university students worked in an online inquiry learning environment on buoyancy and Archimedes’ principle. Students were randomly assigned to one of three conditions, each of which contained a different version of the EDT. Since students’ prior knowledge has been found to influence the amount and type of guidance they need, the versions of the tool differed with respect to the level of guidance provided. A pre- and post-test were administered to assess students’ conceptual knowledge. No overall differences between conditions were found. In a subsequent analysis, students were classified as either low, low-intermediate-, high-intermediate, or high prior knowledge students. For Archimedes’ principle we found that low-intermediate prior knowledge students gained significantly more conceptual knowledge than low prior knowledge students in the fully guided condition. It is hypothesised that students need at least some prior knowledge in order to fully benefit from the guidance offered.

Pengaruh Model Pembelajaran Inkuiri Terbimbing Terhadap Keterampilan Proses Dan Penguasaan Konsep Sains Ditinjau Dari Pengetahuan Awal Peserta Didik

The study intended to discover : 1) the impact of Guided Inquiry Learning Model (henceforth, GILM) towards students scientific processing skills and conceptual mastery which was reviewed from their prior knowleadge (high or low ), 2) the impact of students basic level of knowledge towards their scientific processing skills and conceptual mastery, and 3) the interaction between learning model and students prior knowledge towards their scientific processing skills and conceptual mastery. The study employed quasi experimental method with 2 x 2 factorial analyses. The study was conducted in Junior High School 2 Mataram (SMPN 2 Mataram) in academic year of 2016/2017. The sample of data collection utilized cluster random sampling technique. Both experimental and control groups were consisted of 62 students. Scientific processing skills and conceptual mastery observation sheets were used as research instruments. The data analyzed with Anava with SPSS version 20 for windows. The results showed that 1) there was a significant impact of GILM and conventional learning model towards students’ scientific processing skills and conceptual mastery, 2) there was no significant impact of students prior knowledge towards their scientific processing skills and conceptual mastery, 3) there was no interaction between learning models and students’ prior knowledge towards their scientific processing skills and conceptual mastery.

The Role of Inquiry Based Learning to Improve Reading Comprehension of EFL Students

Approaches in reading have widely emerged to fulfill the needs of learners to comprehend a text and to change their reading habit which is one of them is Inquiry Based Learning (IBL). Thus, this study aims to identify the role of Inquiry Based Learning to improve reading comprehension. The design of this study was mixed method with QUAN-qual model. The quantitative method used quasi-experimental design with control and experimental group including pre-test and post-test. It used purposive sampling technique to determine the samples who involved 40 students; 19 students in control class and 21 students in experimental class. This study was conducted at third semester students of English Education Department of STKIP Muhammadiyah Sidrap. The data were gained through test and non-test (questionnaire and interview). Then, the data were analyzed through SPSS 22. The significant findings of the recent study was the roles of IBL; developing students’ reading proficiency, engaging the students with complex texts, practicing students’ all levels of comprehension as they take a part in IBL phases,activating students prior knowledge, aligning inquiry process to students’ reading comprehension, providing students to work with team and enhancing students’ learning process. Finally, this study could be implemented practically and pedagogically in the study of IBL.

Challenges in Teaching English for the Deaf Students

English is a subject included in the education curriculum in Indonesia.According to the individuals with Disabilities Education Act (IDEA), one of thecategories of students with special needs is deaf students. This paper is aimedto discover the challenges faced by deaf students’ teachers in teaching Englishand the strategies to cope with those challenges based on relevant theoriesand previous studies. The finding showed that teachers experienced severalchallenges in teaching the deaf students such as getting students’ attention,understanding words from students’ lip movements, giving definitions andexample, differentiating similar words in different contexts, and deliveringmaterials related to students prior knowledge. The strategies to cope thosechallenges are asking students to prepare dictionaries, using alphabetic signs,waving or patting students’ shoulders to get their attention. In addition it alsorequires teaching model and professional teacher to be creative and effectivein teaching English for the deaf students.

Using a mathematical model of motivation, volition, and performance to examine students’ e-text learning experiences

This empirical study used Keller’s (Technol Instr Cogn Learn 16:79–104, 2008b) motivation, volition, and performance (MVP) theory to develop and statistically evaluate a mathematical MVP model that can serve as a research and policy tool for evaluating students’ learning experiences in digital environments. Specifically, it explored undergraduate biology students’ learning and attitudes toward e-texts using a MVP mathematical model in two different e-text environments. A data set (N = 1334) that included student motivation and e-text information processing, frustration with using e-texts, and student ability variables was used to evaluate e-text satisfaction. A regression analysis of these variables revealed a significant model that explained 77% of the variation in student e-text satisfaction in both e-text learning environments. Student motivation and intrinsic cognitive load were positive predictors of student satisfaction, while extraneous cognitive load and student prior knowledge and background variables were negative predictors. Practical implications for e-text learning and generalizability of a mathematical MVP model are discussed.

Enhancing students’ mathematical representation and selfefficacy through situation-based learning assisted by geometer’s sketchpad program

This research was conducted based on the problem of a lack of students’ mathematical representation ability as well as self-efficacy in accomplishing mathematical tasks. To overcome this problem, this research used situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP). This research investigated students’ improvement of mathematical representation ability who were taught under situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP) and regular method that viewed from the whole students’ prior knowledge (high, average, and low level). In addition, this research investigated the difference of students’ self-efficacy after learning was given. This research belongs to quasi experiment research using non-equivalent control group design with purposive sampling. The result of this research showed that students’ enhancement in their mathematical representation ability taught under SBL assisted by GSP was better than the regular method. Also, there was no interaction between learning methods and students prior knowledge in student’ enhancement of mathematical representation ability. There was significant difference of students’ enhancement of mathematical representation ability taught under SBL assisted by GSP viewed from students’ prior knowledge. Furthermore, there was no significant difference in terms of self-efficacy between those who were taught by SBL assisted by GSP with the regular method.

SVM and PCA Based Learning Feature Classification Approaches for E-Learning System

E-learning and online education has made great improvements in the recent past. It has shifted the teaching paradigm from conventional classroom learning to dynamic web based learning. Due to this, a dynamic learning material has been delivered to learners, instead of static content, according to their skills, needs and preferences. In this article, the authors have classified eight different types of student learning attributes based on National Centre for Biotechnical Information (NCBI) e-learning database. The eight types of attributes are Anxiety (A), Personality (P), Learning style (L), Cognitive style (C), Grades from previous sem (GP), Motivation (M), Study level (SL) and Student prior knowledge (SPK). In this article the authors have proposed an approach which uses principal components of student learning attributes and have later independently classified these attributes using feed forward neural network (NN) and Least Square –Support Vector Machine (LS-SVM).

Facilitating application of language skills in authentic environments with a mobile learning system

AbstractWe uncovered two critical issues in earlier studies: (a) some studies have shown that mobile learning technology is not beneficial for all students due to complexity of learning environments and student prior knowledge, skills, and experience and (b) familiarity of students with the authentic environments in which they learn using mobile technology did not receive much attention in earlier studies. To address these issues, we designed three learning tasks for a class of 26 junior high school students. The students applied language skills by completing the tasks in authentic environments individually in a first task, loosely collaborating with peers in a second task, and tightly collaborating with peers in a third task. A mobile learning system was also designed in this study to support students to accomplish the tasks. The aim of this study was to explore students' learning experiences using the learning system, their perceptions towards the system, and to assess how differently the students perform on the three tasks. According to our design, in the first task, the students took pictures of objects and described them orally or in writing using the mobile learning system. In the second task, after the students completed assignments, each student received comments from a partner through the system. In comments, the partner indicated flaws in student assignments and suggested how to fix them. In the third task, the students completed assignments, shared them using the system, and then exchanged comments with their partners face to face regarding issues related to their completed assignments and suggested how to improve them. Such learning behaviours in the three tasks enabled the students to practise writing and speaking skills. Our results demonstrate that most of the students highly valued our learning system and intend to use it in the future. Furthermore, the results show that the students performed best when they collaborated; namely, student performance was enhanced the most after the third task that required tight collaboration. Based on our results, we learned that students' familiarity with authentic environments is very important and beneficial for their learning. In addition, we learned that even in complex environment, less skilled and experienced students with low prior knowledge can perform well when they tightly collaborate with more skilled and experienced students with high prior knowledge, and our learning system can facilitate such collaboration.

Developing Food Science Core Competencies in Vietnam: The Role of Experience and Problem Solving in an Industry‐Based Undergraduate Research Course

AbstractAlthough many educators now recognize the value of problem‐based learning and experiential learning, undergraduate‐level food science courses that reflect these pedagogical approaches are still relatively novel, especially in East and Southeast Asia. Leveraging existing partnerships with farmers in Vietnam, a food science course for students at Nong Lam Univ. was designed and taught. The aim was to give students the opportunity to work in small groups and conduct evidence‐based research with farmers, apply food science principles, and develop Success Skills, including the ability to think critically and communicate clearly. Drawing on the experience of 2 student groups, this exploratory study describes what students learned from the process of conducting research. In one group, students learned to work through and resolve the challenge of initial disagreement and misunderstanding with farmers and ultimately carried out a project that aligned with the students’ research interests and farmers’ needs. Another group of students learned to consider the financial limitations of farmers when attempting to develop solutions for problems and ultimately worked with farmers to address a different problem that was less financially taxing. It is important to note the challenges of planning and teaching a course in which instructors are not able to predict exactly what students will learn or experience. This is largely dependent on each student's prior knowledge, experiences, and interests; yet this study demonstrates the transformative potential of teaching a research‐based food science course that gives students authentic opportunities to identify and address real‐world challenges.

Constructing activity–mobility trajectories of college students based on smart card transaction data

Abstract In this research, we use UB card as a convenient source of combined smart transaction data in order to define a campus-wide model for constructing students’ activity–mobility trajectories in time–space dimension. UB Card is a student’s official ID at the University at Buffalo and is used across campus for various activities including Stampedes and Shuttles (on-campus bus system), facilities access, library services, dining, shopping, and etc. Two activity–mobility trajectory construction algorithms are developed. The base algorithm constructs students’ activity–mobility patterns in space–time dimension using a set of smart card transaction data points as the only inputs. The modified individualized algorithm constructs activity–mobility patterns with prior knowledge of students’ previous patterns as they have similar patterns for certain days of the week. A database of 37 students’ travel survey and UB card transactions that contains a period of 5 days have been used to illustrate the results of the study. Three measures of errors have been proposed to capture the time allocation, location deviation, and activity sequences. These errors present an acceptable accuracy (12–25% error ranges for activity types and average 0.04–0.16 miles of error for location predictions) and show the potential of inferring activity–mobility behaviors based on smart card transaction type data sets.