Enhancing Learning Performance Research Articles

Enhancing Learning Performance Through Classroom Response Systems: The Effect of Knowledge in a Global Economic Environment

ABSTRACTThe international business education literature suggests that a global mindset can be acquired and benefit students to embrace new ideas and improve their critical thinking. Using a sample of 1,448 undergraduate students in Corporate Finance, International Finance, and Business Law subjects during 2013–2015, our results indicate that students with better academic performance in the subject Global Economic Environment achieve a better learning outcome in advanced functional business subjects. However, students with a better global mindset do not benefit as much from the Classroom Response Systems (CRSs) as the weaker students do.

Enhance e-learning system performance with a cloud and crowd-oriented approach

There are several e-learning systems focusing on the flipped classroom concept. The basic concept of flipped classroom is to have students learn by themselves. Once the background learning stage is performed outside of the class time, tutors have free time to lead students to participate in higher-order thinking. However, as shown in the report of Ash (2012), the performance of the flipped classroom method is arguable. Our survey shows that the contents offered by most modern e-learning systems are relatively static. Considering how fast new information appears on the web, creating content requires effort. The work load of our teachers is already heavy, so expecting teachers to update contents very frequently is not practical. Besides, crowd intelligence is usually considered helpful in enhancing learning performance. In this research, a system to utilise both cloud materials and crowd intelligence is proposed and an experiment to validate the system is included.

Enhance e-learning system performance with a cloud and crowd-oriented approach

There are several e-learning systems focusing on the flipped classroom concept. The basic concept of flipped classroom is to have students learn by themselves. Once the background learning stage is performed outside of the class time, tutors have free time to lead students to participate in higher-order thinking. However, as shown in the report of Ash (2012), the performance of the flipped classroom method is arguable. Our survey shows that the contents offered by most modern e-learning systems are relatively static. Considering how fast new information appears on the web, creating content requires effort. The work load of our teachers is already heavy, so expecting teachers to update contents very frequently is not practical. Besides, crowd intelligence is usually considered helpful in enhancing learning performance. In this research, a system to utilise both cloud materials and crowd intelligence is proposed and an experiment to validate the system is included.

An Adaptive e-Learning System for Enhancing Learning Performance: Based on Dynamic Scaffolding Theory

Adaptive learning for individual learners has recently become popular in education. This study aims to fill the void in the existing literature by building an adaptive e-learning system with self-assessment rubrics based on the dynamic scaffolding theory in response to different student needs. Meanwhile, the purpose of this study is to explore the effectiveness of using adaptive e-learning with dynamic scaffoldings and rubrics in fostering students’ learning outcomes. An experimental design was conducted to evaluate learning effectiveness and learning satisfaction in the Excel (spreadsheet) of the course for using the developed adaptive e-learning system. Sixty undergraduate students from a technology university in central Taiwan participated in this experimental study and executed a pretest and a posttest. Research results revealed that the developed adaptive e-learning system can effectively support students with personalized learning materials and successfully helps students acquired knowledge and develop cognitive abilities. The results recommend that teachers could employ rubrics as a self-assessment tool for supporting students with dynamic scaffoldings to conduct a learner-centered e-learning environment. Additionally, the lack of generalizability is clearly a limitation of the present data due to a few participants. Finally, future research direction of this study was also discussed.

AR‐based value‐added visualization of infographic for enhancing learning performance

AbstractAugmented reality‐based infographic is an edutainment media that can play a significant role in transferring complicated issues for learning purposes. It has the potential to draw participant's attention to visualize various kinds of information including text, image, animation, 3D objects, etc. on infographic using smatphones and tablets. This paper discusses the effect of AR‐based infographic on improving learning performance via T‐Paired test and in the meantime the correlation between participants’ learning style based on Felder–Silverman model with their quadratic Bloom‐based knowledge. Experimental results confirm the usability of AR‐based infographic in improving learning performance and its impact on visual type participants no matter which kinds of knowledge they are equipped with.

Multi-train: A semi-supervised heterogeneous ensemble classifier

Many real-world machine learning tasks have very limited labeled data but a large amount of unlabeled data. To take advantage of the unlabeled data for enhancing learning performance, several semi-supervised learning techniques have been developed. In this paper, we propose a novel semi-supervised ensemble learning algorithm, termed Multi-Train, which generates a number of heterogeneous classifiers that use different classification models and/or different features. During the training process, each classifier is refined using unlabeled data, which are labeled by the majority prediction of the rest classifiers. We hypothesize that the use of different models and different input features can promote the diversity of the ensemble, thereby improving the performance compared to existing methods such as the co-training and tri-training algorithms. Experimental results on the UCI datasets clearly demonstrated the effectiveness of using heterogeneous ensembles in semi-supervised learning.

Enhancing learning performance, attention, and meditation using a speech-to-text recognition application: evidence from multiple data sources

ABSTRACTIn this study, we provide STR-texts to non-native English speaking students during English lectures to facilitate learning, attention, and meditation. We carry out an experiment to test the feasibility of our approach. Our results show that the participants in the experimental group both outperform those in the control group on the post-tests and have higher attention and meditation. In addition, our results demonstrate that lower ability students who used STR-texts had higher learning performance, attention, and meditation than lower ability students in the control group. The results also show that attention and meditation are dynamic and change throughout the lectures. Furthermore, we found that attention trendlines have a negative slope, whereas meditation trendlines have a positive slope. Our results suggest that STR-texts are useful for non-native speaking students, especially those with lower language proficiency, and can enhance their comprehension of English lectures and also raise their attention and meditation. However, educators and researchers should keep in mind that interactive strategies need to be applied in order to maintain and even increase low proficiency student attention throughout the lectures.

Technology-enhanced Learning in Science, Technology, and Mathematics Education: Results on Supporting Student Learning

To prepare students to be creative and lifelong learning individuals in a rapid growth in science, technology, and mathematics (STM), technology in education plays an important role for enhancing learning performance. In the recent years, researchers have demonstrated the pivotal influences of technological personalized learning environments based on the concept-effect relationship model on student learning performance improvement. Such learning environment has been demonstrated to be useful for helping teachers to diagnose learning problems for individual students according to test answers, and to provide personalized remedial learning guidance for improving students’ learning performance. Teachers can also use the knowledge gained from this system to choose learning materials that are appropriate for personalized student. To show effectiveness of technological personalized learning environments based on the concept-effect relationship model, this paper presents the results on supporting student conceptual learning in several areas such as mathematics, science, and computer science. Moreover, the guideline for researchers/practitioners is also presented at the end of this paper.

Experience-dependent regulation of zif268 gene expression and spatial learning

Environmental enrichment (EE) is known to enhance the cognitive ability of rodents. To translate EE to the human condition, it is important to understand the parameters of its efficacy. In this study, we examine if the cognitive enhancement associated with EE is permanent and whether a developmental window exists for its efficacy. Rats were housed in continuous isolation (ISO), continuous enrichment (EE), enrichment from postnatal day (PN) 21-50, and then isolation from PN50-79 (PM), or isolation from PN21-50 and then enriched from PN50-79 (CW). Spatial learning ability and basal expression of the immediate-early genes zif268 and Arc as well as the NR1 subunit of the NMDA receptor were assessed. Rats housed in an enriched environment at the time of testing (EE and CW) performed significantly better in the spatial learning task than rats housed in an isolated environment at the time of testing (ISO and PM). Enhanced performance in the spatial learning task was associated with a higher expression of zif268 only in the CA3/CA4 region of the hippocampus. Our study further defines parameters that make environmental enrichment effective in enhancing learning performance and the findings may be helpful in the translation of this intervention to the human condition.

Single, intense prenatal stress decreases emotionality and enhances learning performance in the adolescent rat offspring: Interaction with a brief, daily maternal separation

Perinatal manipulations can lead to neurobehavioural changes in the progeny. In this study we investigated, in adolescent male rat offspring, the consequences of a single, intense prenatal stress induced by a 120 min-maternal immobilization at gestational day 16, and of a daily, brief maternal separation from postnatal day 2 until 21, on: unconditioned fear/anxiety-like behaviour in open field and in elevated plus-maze; learning performance in the “Can test”, a non-aversive spatial and tactile/visual task; corticosterone plasma levels under basal and stress-induced conditions. Our results indicate that both prenatal stress and maternal separation procedures decrease emotionality and enhance learning performance. Maternal separation potentiates prenatal stress-induced effects in enhancing learning performance. Both basal and stress-induced corticosterone plasma levels are reduced following prenatal stress, maternal separation and the combination of two procedures. These findings suggest that a single, intense prenatal stress can enhance the adaptive stress-related responses in the progeny, probably due to the involvement of maternal factors. The synergistic effect of prenatal stress and maternal separation on learning performance may be due to a further damping of hypothalamic–pituitary–adrenal axis response in the progeny that better cope with the task administered.

Use of Group Discussion and Learning Portfolio to Build Knowledge for Managing Web Group Learning

To monitor and enhance the learning performance of learning groups in a Web learning system, teachers need to know the learning status of the group and determine the key influences affecting group learning outcomes. Teachers can achieve this goal by observing the group discussions and learning behavior from Web logs and aanlyzing the Web log data to obtain the relevant information. However, Web logs are not systematically organized and the discussions are extensive. Consequently, teachers must struggle to extract information from logs and intuitively apply teaching rules based on experience when managing the groups. Rather than using statistics packages to evaluate hypotheses, this work presents a methodology of applying existing data and text mining tools to automatically gather learning status and predict performance of learning groups from the contents of discussions and from log records of learning behaviors. Meanwhile, the methodology infers a causal network exists between learning features and learning performance. Knowledge is inferred based on statistics and probability reasoning and social interdependency theory. The causal network can suggest means of enhancing learning performance to teachers. Simultaneously, teachers can use the knowledge of learning groups obtained to manage group learning process on the Web. Experimental results of applying the novel methodology to manage a group learning class organized over the Web and containing 706 students are also presented.

Enhancing Self-Efficacy and Learning Performance

The effect of a communication designed to enhance the self-efficacy beliefs of introductory psychology students was examined. The author assigned students (N = 123) into above average, average, and below average performance categories. All students were invited to send the author an e-mail to receive a bonus point. Of the students who responded (n = 76), half were sent an e-mail message designed to enhance their efficacy beliefs, while the other half received a neutral note. As predicted, self-efficacy beliefs were significantly related to exam scores and significantly affected by the efficacy-enhancing communication.