A synchronous distance discussion procedure with reinforcement mechanism: Designed for elementary school students to achieve the attending and responding stages of the affective domain teaching goals within a class period

Distance education courses must cope with the difficulties imposed by delivering a class at a distance. As most courses only emphasize the cognitive aspects of the class and neglect the course’s effect on the students, this gives no help for reaching the affective domain teaching goals. Especially for younger students, in distance education, when younger students are out of the sight of teachers, they could easily be distracted by the environment around them. This research outlines a synchronous discussion procedure with reinforcement mechanism designed for elementary school students to integrate the affective aspects of teaching into distance education within a class period. The mechanism allows teachers to understand students’ attitudes within the class and provides instant feedback to the teacher. Learners can also get information about their attitudes and help to reach the affective domain teaching goals of the courses. This mechanism was implemented and investigated. Comparative assessments were made by administering interviews and questionnaires to elementary school students. The results show that the procedure can supervise learners and help them reach the response stage of the affective domain teaching goals.     

A synchronous distance discussion procedure with reinforcement mechanism: Designed for elementary school students to achieve the attending and responding stages of the affective domain teaching goals within a class period

Distance education courses must cope with the difficulties imposed by delivering a class at a distance. As most courses only emphasize the cognitive aspects of the class and neglect the course’s effect on the students, this gives no help for reaching the affective domain teaching goals. Especially for younger students, in distance education, when younger students are out of the sight of teachers, they could easily be distracted by the environment around them. This research outlines a synchronous discussion procedure with reinforcement mechanism designed for elementary school students to integrate the affective aspects of teaching into distance education within a class period. The mechanism allows teachers to understand students’ attitudes within the class and provides instant feedback to the teacher. Learners can also get information about their attitudes and help to reach the affective domain teaching goals of the courses. This mechanism was implemented and investigated. Comparative assessments were made by administering interviews and questionnaires to elementary school students. The results show that the procedure can supervise learners and help them reach the response stage of the affective domain teaching goals.     

Assessment of affective state in distance learning based on image detection by using fuzzy fusion

Distance learning can solve the limitations of time and space in learning. However, due to the distance, teachers cannot manage students learning behaviors, i.e. they do not know whether a student is attentive, drowsy or absent. Teachers can overcome difficulties in students’ management by knowing the affective states of the students. This study adopts image recognition to capture face images of students when they are learning, and analyzes their face features to evaluate their affective states by fuzzy integrals. Test results indicate that the bad affective states are accurately identified. Teachers can monitor the students’ affective states from the detection results on the system interface.     

Teacher-created video instruction in the elementary classroom—Its impact on students and teachers

Despite the proliferation of multimedia devices in elementary classrooms, there is limited research examining teacher-created video instruction, particularly regarding its effect on academic growth and engagement. This study investigated the effect of teacher-created computer-based video instruction (CBVI) using iPads on students' academic, behavioural and affective learning in elementary classrooms. The study used a repeated-measures design with counterbalancing to measure the effects of CBVI during mathematics lessons on student achievement scores, time on-task and attitudes towards learning. Three year three classes (n = 49) completed three lessons, each using a different mode of instruction: CBVI created by the class teacher, CBVI created by a stranger, and a traditional live lesson delivered by the class teacher. Results were analysed using a Linear Mixed Model. No significant growth in performance was detected during video instruction, however a significant growth result was achieved for the traditional live teaching mode (p < 0.001), possibly attributable to the longer duration of experimental session. Behavioural engagement was considerably higher during CBVI lessons than live lessons and students preferred their teacher's voice during CBVI. Three teachers were interviewed to examine how CBVI affected teaching and learning, with two main themes emerging: (1) positive impacts of CBVI upon students; and (2) positive impacts on teacher wellbeing. This research indicates benefits for students and teachers when using teacher-created CBVI. Further research is needed to better understand the factors that influence cognitive development of students using CBVI and to also further explore the effect of CBVI on teacher wellbeing.     

基于Excel的学生成绩统计与分析系统

为了对教师的教学成果和学生学习情况作出科学的定量评价,学生成绩在统计、汇总以后要进行学分计算、正态分布分析以及制作不同形式的成绩单,这需要花费教师大量宝贵的时间。借助电子表格Excel强大的数据交换与处理功能,进行学生成绩的统计与分析,可以大大减轻教师的重复工作量,提高工作效率,促进教学水平的提高。     

Intelligent preference selection model based on NRE for evaluating student learning achievement

In order to evaluate student learning achievement, several aspects should be considered, such as exercises, examinations, and observations. Traditionally, such an evaluation calculates a final score using a weighted average method after awarding numerical scores, and then determines a grade according to a set of established crisp criteria. However, this approach lacks the potential to reflect the individual characteristics of a class compared to others. Several researches have used fuzzy techniques to devise practical methods for evaluating student learning achievement to ascertain linguistic terms that are usually used by teachers to assess student learning achievement. However, these approaches are largely based on expert opinions and require complicated computational processes. In this paper, we present a new method for evaluating student learning achievement using an adaptive ordered weighted averaging operator and K-nearest-neighbor classification method. The proposed method simulates the evaluation behavior of teachers when performing a student achievement evaluation based on a norm-referenced evaluation by identifying situations involving the application of intelligence and provides a useful means to award a reasonable grade to students. Furthermore, the proposed method provides a feedback mechanism to update the norm dataset. Therefore, the repetitious use of the feedback mechanism will gradually strengthen the representativeness of the norm dataset.     

The interactive use of a video database in teacher education: Creating a knowledge base for teaching through a learning community

This study explores how pre-service student teachers acquired knowledge of good teaching practices through the interactive use of a video database and an online discussion forum, where the student teachers shared their teaching videos and received comments or suggestions from members of a learning community. A small group of student teachers was involved in this collaborative learning community during their teaching practicum in their third and fourth years of study. Content analysis of the sharing in the discussion forum and individual student teacher reflections provides insight into the use of a collaborative learning community to create a knowledge base for teaching. Suggestions regarding how this new technology can support teacher education are discussed.     

基于均值聚类和决策树算法的学生成绩分析

 针对高职学生的学习情况,采用k-均值聚类算法对学生的考试成绩进行等级划分,再采用R-C4.5算法构造决策树,通过对该决策树提取规则来分析学生各学科成绩和总评成绩的相关性。该方法可以减少决策树中的无意义的分支,挖掘出影响学生总评成绩的主要因素,为任课教师和教学管理人员在制定教学计划、开展教学工作和进行教学评价等方面提供参考。     

Constructing collaborative learning activities for distance cal systems

Many existing Computer Assisted Learning (CAL) systems use computer programs to simulate a teacher for individual learning. However, regardless of how good the CAL system is, a student should also interact with learning companions and human teachers. Due to the popularity and ease of access to computer networks and communication tools, network facilities can be incorporated into a CAL system to make it a distance CAL system. To attain an effective learning outcome, a distance CAL system must be able to: define a group learning model; constrain and advise the students to learn according to the model, and have query facilities which provide the teacher with information about what a student has done and learned, and what a student should do next. A rule‐based system that is conventionally used cannot sufficiently provide those required functions. This paper suggests why this is the case and how an active database system can achieve those goals. Distance CAL     

EcoMOBILE: Integrating augmented reality and probeware with environmental education field trips

Positioned in the context of situated learning theory, the EcoMOBILE project combines an augmented reality (AR) experience with use of environmental probeware during a field trip to a local pond environment. Activities combining these two technologies were designed to address ecosystem science learning goals for middle school students, and aid in their understanding and interpretation of water quality measurements. The intervention was conducted with five classes of sixth graders from a northeastern school district as a pilot study for the larger EcoMOBILE project, and included pre-field trip training, a field trip to a local pond environment, and post-field trip discussions in the classroom.During the field experience, students used mobile wireless devices with FreshAiR™, an augmented reality application, to navigate the pond environment and to observe virtual media and information overlaid on the physical pond. This AR experience was combined with probeware, in that students collected water quality measurements at designated AR hotspots during the experience. We studied the characteristics of learning and instruction using measures of student attitudes, content learning gains, and opinions teachers provided via written and verbal feedback. We observed gains in student affective measures and content understanding following the intervention. Teachers reported that the combined technologies promoted student interaction with the pond and with classmates in a format that was student-centered rather than teacher-directed. Teachers also reported that students demonstrated deeper understanding of the principles of water quality measurement than was typical on prior field trips without these technologies and that students had expanded opportunities to engage in activities that resemble scientific practice. Overall, results of the students' surveys and teacher feedback suggest that there are multiple benefits to using this suite of technologies for teaching and for learning.