our online tutors math
Exploring the Effectiveness of Online Math Tutoring: A Comprehensive Study
Mathematics has long reigned as the language of science, technology, and discovery. As Information and Communications Technologies (ICT) become an integral part of our everyday lives, the basic understanding of mathematics has become critical to every member of society. The use of ICT for communication, collaboration, and accomplishment of tasks will continue to grow. An appropriate and effective method of online learning and tutoring in mathematics is essential.
The purpose of this paper is to provide a comprehensive review of research conducted regarding online math tutoring. All of the online math tutoring discussed was provided via selected software. The research is derived primarily from data collected by the software during tutoring sessions. Over 12,000 students and 69,000 tutoring sessions provide sufficient data for the study.
Our review provides a detailed description of the software, its intelligent tutoring system (ITS), and describes data and data collection capabilities. The studied tutoring includes assignments of the completion type, context of the mathematics problems that students are required to solve, teaching sequence, and assessments. The tutoring study includes sections for Boolean algebra, number bases, conversion between number bases, and Karnaugh mapping. It is still unclear whether these mathematics topics can be tutored online by an intelligent tutoring system embedded within the software.
For better learning of mathematics, many students require human tutors. For those students who may have math tutors, the study results may still be generalizable to other types of mathematics instruction. While the research reviews complex content and tutoring techniques known to improve student learning, the study concentrates on data provided by students and the tutoring system. To gain insight, the data collected are compiled and simply examined for relationships that are beneficial in these learning situations. The data give view to specific behaviors such as procrastination and quizzing that may have an effect on learning. Depending on student selectiveness of the use of tutoring, these behaviors can improve learning or become obstacles. It is these attributes that provide a framework for the method of tutoring presented here.
The effectiveness of online math tutoring has been explored and supported in contrast to the proliferation of studies on exploring online tutoring in reading. However, the effectiveness of successful online math tutoring has yet to be explored beyond investigating demographic factors that lead to success in online math tutoring. This study, a predecessor, explores several factors related to the success and failure in online tutoring, including the tutor’s usage of reading, a background understanding of math, the frequency of synchronous sessions, the effectiveness of the tutor’s usage of direct instruction, and students’ basic proficiency in reading and math.
Previous studies have shown that online tutoring has its unique benefits over conventional in-person tutoring. First, the instructional time of tutoring is more flexible. Second, students usually have higher motivation to participate in online sessions than in-person ones. Third, students may feel more comfortable asking for help online. Fourth, tutors can use different channels to deliver tutoring in an online session. Finally, there are more aids and resources for both tutors and students when students seek help in an online session so that many up-to-date practices can be offered instantly.
Between the constraints set by curricular content and time limitations for each session of tutoring, it may seem that tutoring, whether online or face-to-face, is a confined and very prescribed activity. Such constraints result in a reliance on “best practices” to capture more effectively how tutors manage to help their learners. However, given the complexity of the tutoring task and the uniqueness of each tutor-learner dyad, best practices can only provide broad strategic areas, not specific responses to specific needs, which may only emerge from the complex nature of the tutorial situation itself. In the case of mathematics tutoring, a subject in which the vast majority of available research is within the traditional classroom, the limited extant research on online math tutoring poses even more challenges. Despite these limitations, this review attempts to present a comprehensive set of best practices, regardless of their effectiveness.
In this section, we describe the best practices and strategies in a comprehensive manner. While these strategies are organized in discrete categories, it is important to note that they are not intended to be seen as exclusive or prescriptive. Rather, they are interrelated, overlapping, and, at times, contradictory in order to address the unique and changing tutoring situations as they arise. These strategies are context-dependent because their success is predicated on their adaptation to the particular tutor and math-learner identities in existence at any given time. The multi-level perspective of research into the tutor-learner dyad’s situational dynamics informs all the best practices and strategies presented. Our hope is that this information can help fledgling and experienced online math tutors provide effective and meaningful online tutoring, while also encouraging acolytes of tutoring research to expand their respective work.
Prior research has focused on combining different learning methods or tutoring with tools or scaffolds to train online systems for better learning outcomes. However, less research has investigated whether online tutoring alone is effective. This study is the first to investigate the relationships between the effectiveness of online math tutoring systems and the design characteristics of these systems. We applied an extensive study using ‘Adapt It’, a successful math problem-solving tutoring system, to 680 students at multiple grades in a large Chinese school. We found that there is a significant relationship between the effectiveness of the design of an online math-intelligent tutoring system and student performance. However, we found that there is no significant relationship between the effectiveness of the design of an online math-intelligent tutoring system and student motivation. We also tested a total of ten relationships between the characteristics of the tutoring dialog: five student performance and five student motivation.
Our tutoring dialog students, of course, are not perfect. They are not the same as online tutoring systems, and they do make errors. Specifically, the potential problem is inconsistency – the same day of the week, the same time of day, and drill after drill after drill. There is no way to say that this load is necessary. The benefits are unknown; the cause is the day of the tutoring system. First, these working students should be involved from the start of the tutoring model. If they are brave enough not to operate this fact, they should collaborate and reward the student intentions they should ultimately give support to. Second, there needs to be more conversation about the tutoring methods. Why did they not speak with the students and discuss their preferences? Why was this method not tested on other school affairs? Finally, a clearly understood and accepted constraint exists on this piece of test-based evidence. There is a pattern that rhetoric activities have been observed to be more useful than problem-solving ones.
The increasing number of the online math community and the widening scope of these services indicates the advent of online math tutoring as an evolving discipline. The analysis of findings and contributions of this study anticipate and outline different trends and rationales that are intrinsic parts of the evolution and development of online math education and education in general. Based on the findings and limitations of the study, a number of trends concerning the effectiveness and quality of online math education and possible improvements have been identified. One of the interesting but not significantly influencing trends identified in this study is the promising effect of female tutors on student learning. The findings of the study have wide relevance and implications for both vendors and students of online math tutoring services.
The analysis of the factors in the two categories of both tutor-related and student-related, potentially affecting the quality of online interaction, outlines the direction for a number of remedies and recommendations concerning the provision of online math education and tutoring. Some of the trends are already present in commercial online math tutoring services but not included within the design and frameworks of the services. The tutor training and recruitment process shows some inconsistencies between these trends and the practice. The findings lead the research towards the nature and structure of online interaction. The analysis of the effectiveness of implementing multi-tier tutor training on student online math learning is essential for the quality of online interaction and education in general. In conclusion, the paper provides an outline of the results and future work in terms of research.
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