An Investigation on the Influence of Middle School Students'Grammar Learning Self-efficacy on Their Learning Performance

In middleschool English teaching,grammar instruction has always been an important and challenging aspect.Due to the strong influence of grammar explanation in Chinese,learning English grammar may be affected by negative transfer from their native language,which could pose certain obstacles to English acquisition.Self-efficacy,as a major emotional factor influencing learners'internal regulation strategies,has attracted wide attention from researchers both domestically and internationally for its impact on learning performance.High self-efficacy helps learners develop a more positive mindset towards learning,thereby contributing to improved learning performance.Therefore,this study focuses on investigating the relationship between grammatical self-efficacy and learning performance of English grammar among middle school students.This research contributes to a complementary understanding of grammatical self-efficacy among educators,enhancing their teaching skills,and effectively guiding students to learn English grammar with a more positive and healthy mindset,presenting a future grammar instruction in middle school English teaching.

Evaluation of Chinese Learning Efficiency of International Students in China:Comparing by Dimension

This paper introduces the Value Engineering method to calculate the value coefficient of Chinese learning efficiency for 377 international students by dimension.Results suggest that attention should be paid to male,European and American,rural,introverted,and“work or education needs”international students;Give full play to the driving role of the reference-type,explore the space for improving the learning efficiency of the improvement-type and attention-type,and pay attention to the problems of problem-type international students.

Evaluation of Chinese Learning Efficiency of International Students in China

This paper investigates the related factors of Chinese learning engagement and performance of 377 students from three universities in Guangzhou of China,employs the value engineering method,and calculates the value coefficient of learning efficiency.From the value coefficient of Chinese language learning,it proves that over 60%of international students studying in China have a higher efficiency in learning Chinese.

The effect of classroom wall color on learning performance: A virtual reality experiment

The wall color has the certain impact on the learning performance of college students in the classroom.To find the suitable wall color to improve the learning performance,this study used the virtual reality(VR)technology to build five virtual classrooms with yellow,red,white,blue,and green walls,while the subjective evaluation and objective physiological indicators of college students were collected.The subjective survey showed the cold-colored walls such as blue and green had the highest levels of relaxation and pleasure,while the warm-colored walls such as yellow and red had the better attention and learning performance.And the white-walled classroom had the lowest subjective evaluation and the worst learning performance,but the white wall was widely used in the present class room.Physiological test results showed the yellow wall had the higher HRV-nLF/nHF and low-β&high-βfrequencies in the FP2 channel in the frontal,but the white wall had the lowest scores.Moreover,the correlation analysis had confirmed electroencephalography(EEG)and electrocardiogram(ECG)indicators could be employed to evaluate the learning performance.These findings provide an effective reference for the spatial design of university classrooms and a basis for the study of physiological indicators.

Effects of In-video Questions and Feedback on Learning Performance

The eye-tracking technology was used in this study to investigate the effects of embedded questions and feedback in instructional videos on learning performance and attention allocation and whether an expertise reversal effect existed.The experiment involved 49 learners with high-level prior knowledge and 45 ones with low-level prior knowledge from a university.Meanwhile,they learned instructional videos with no embedded feedback,embedded questions without feedback and embedded questions with feedback.Findings from the experiment showed that the instructional videos with embedded questions but without feedback not only improved the participants’attention but also enhanced their learning performance.Furthermore,there was an expertise reversal effect on the learning performance whereby instructional videos with embedded questions but without feedback improved the learning performance of learners with low-level prior knowledge,but not those with high-level prior knowledge.

Project-based Learning （PBL） for Enhancing Chinese College Students＇ English Performance

Project-based learning （PBL） as an instructional approach focuses on student-centeredness through contextualizing learning by presenting students with real world issues and practices that aim at achieving enduring learning effects. As a challenge to traditional lecture-based instruction, PBL may generate positive backwash assessment effects via documenting the process of developing authentic language skills. These skills-oriented outcomes are achieved through proper curricula in appropriate learning situations via various dimensions. However, problems may occur such as management, pressure from administration, evaluation doing their selected projects. teacher/student attitude, class size and proper group process and criteria, and students＇ likely frustrations in

Language Assessment Feedback Towards Pedagogical Conversational Agent

Continuous development of technology provides an opportunity to incorporate feedback in online assessments.The mode of online instruction during the pandemic was the most significant survival change.Technology enabled every teacher and student to enter a virtual classroom to make sense of education.Feedback is part of language instruction and is a powerful key to improving students’learning performance.Feedback plays an influential and crucial role in teaching and learning.Feedback is an invaluable,ultimate learning tool for learners that aids them in not committing the same error again and creates impetus.Thus,knowing about formative exam feedback is students’right because quality feedback allures them.Given students’eagerness,providing feedback is considered a good practice to be followed by all the teaching faculty.Apropos of online feedback,the present study attempts to study how pedagogical agents provide online feedback in language assessments.The study also considers the characteristics of pedagogical conversational agents that are suitable for providing feedback in online language assessment.Simply put,the study encapsulates that screen agents play an essential role in students’motivation and acceptability of learning through feedback.

The Influence of Distance Cue on Learning andMetacognitive Monitoring in Classroom

The teaching context is highly related to student’s learning process and the corresponding performance. The current study exploredthe influence of distance cue (the front seats or the back seats in a classroom) on individual’s metacognition and performance. Theresults showed that participants seated in the front seats had higher JOLs and better perform than those in the back seats, and seatinghabits seem to have little impact on these scores. However, this superiority is only related to the participants who believed in that“position of the seat affects learning performance”. The results demonstrated that cognitive process and metacognitive process areaffected by the distance cues in the classroom. Importantly, individual’s belief plays a moderating role.

The Effects of Augmented Reality on Students' Performance, Motivation and Cognitive Load in Distance Education

This study applies augmented reality(AR)to design an experiment to explore the academic performance,motivation and cognitive load level of students in distance education when leaning about communications engineering courses.The samples were 62 distance education students,consisting of 42 part-time adult students from a school of network education and 20 full-time students form a university,all of whom studied remotely in the experimental course.The results show that augmented reality can help distance education students improve their academic performance.As for learning motivation,the enhancement effect is not significant.The study also found that the use of AR did not increase students'cognitive load as long as the guidance was appropriate.

Instance-Specific Algorithm Selection via Multi-Output Learning

Instance-specific algorithm selection technologies have been successfully used in many research fields,such as constraint satisfaction and planning. Researchers have been increasingly trying to model the potential relations between different candidate algorithms for the algorithm selection. In this study, we propose an instancespecific algorithm selection method based on multi-output learning, which can manage these relations more directly.Three kinds of multi-output learning methods are used to predict the performances of the candidate algorithms：（1）multi-output regressor stacking;（2） multi-output extremely randomized trees; and（3） hybrid single-output and multioutput trees. The experimental results obtained using 11 SAT datasets and 5 Max SAT datasets indicate that our proposed methods can obtain a better performance over the state-of-the-art algorithm selection methods.

Transparent open-box learning network and artificial neural network predictions of bubble-point pressure compared

The transparent open box(TOB)learning network algorithm offers an alternative approach to the lack of transparency provided by most machine-learning algorithms.It provides the exact calculations and relationships among the underlying input variables of the datasets to which it is applied.It also has the capability to achieve credible and auditable levels of prediction accuracy to complex,non-linear datasets,typical of those encountered in the oil and gas sector,highlighting the potential for underfitting and overfitting.The algorithm is applied here to predict bubble-point pressure from a published PVT dataset of 166 data records involving four easy-tomeasure variables(reservoir temperature,gas-oil ratio,oil gravity,gas density relative to air)with uneven,and in parts,sparse data coverage.The TOB network demonstrates high-prediction accuracy for this complex system,although it predictions applied to the full dataset are outperformed by an artificial neural network(ANN).However,the performance of the TOB algorithm reveals the risk of overfitting in the sparse areas of the dataset and achieves a prediction performance that matches the ANN algorithm where the underlying data population is adequate.The high levels of transparency and its inhibitions to overfitting enable the TOB learning network to provide complementary information about the underlying dataset to that provided by traditional machine learning algorithms.This makes them suitable for application in parallel with neural-network algorithms,to overcome their black-box tendencies,and for benchmarking the prediction performance of other machine learning algorithms.