Curriculum Development in Mathematics

Introduction

Instituting changes to learning designs is part of curriculum development processes for many learning institutions. Curricula guide how learning should occur and inform decisions responsible for allocating educational resources (Hill et al., 2021). This paper presents a case for the design extension of a learning program intended to improve education outcomes in mathematics among GCSE students in the UK. Key sections of this paper demonstrate the importance of extending group design plans to align learning strategies with educational materials and students’ leaning outcomes to have a comprehensive representation of educational design outcomes.

Characteristics of the New Take

In the current educational design, mathematics is the main educational challenge under assessment. The decision to select mathematics as the focus of the program is informed by low levels of interest and performance in this subject area (Philip and Gupta, 2020). To increase interest in this subject area, the current course design intends to achieve student and teacher objectives. This is a useful feature of the present educational plan because it promotes stakeholder engagement at student and teacher engagement levels (Jain and Kaur, 2021). However, it is prudent to refocus the primary goal of the educational design to create better synchrony with learning strategies, available educational material, and learner experiences.

The aforementioned take on the educational design of the curriculum expands the list of motivations for developing its design from the current three, which include plans to improve students’ mathematics abilities, minimize their lack of interest in the subject area, and promote real-life application of core concepts. Therefore, a fourth one should be included in the list to improve synchrony with learning strategies, available educational material, and learner experiences. This approach to design development is likely to create synergy across different levels of learning (Hill et al., 2021). Adopting this proposal would make the design more encompassing and holistic in the manner it assesses student attitudes and outcomes. Therefore, the motivations for implementing the curriculum plan should be redefined to be holistic.

The proposed redefinition of the educational challenge is supported by poor levels of stakeholder engagement at different levels of leadership. Notably, some students have shown contempt for mathematics, as a useful subject area because of the failure to links its usefulness with their daily lives (Philip and Gupta, 2020). At the same time, some students have expressed their skepticism about the importance of increasing their numeracy skills because they are unsure of their relevance to their lives (Hill et al., 2021). This attitude is prevalent among students studying both mathematics and sciences because researchers, such as Metli and Özcan (2021) and Hill et al. (2021) say that such attitudes do not only exist among students studying mathematics but the sciences as well. In this regard, the current focus of the investigation should be recalibrated to create consistency between students’ learning activities and their real life experiences.

The new take on the curriculum design will create a better alignment between students’ needs and learning activities because both need to be present to generate interest in learning activities. The importance of expanding motivations for implementing the current learning design is to embrace the cross-disciplinary nature of its learning activities because it is multi-layered and has different areas of weakness that are vulnerable to students’ apathy in learning (Alan, Zengin and Kececi, 2021; Zhang and Seah, 2021). The new take on the learning design strives to explain the natural world through learning activities, thereby improving the vitality of education. Therefore, it is important to redefine the objectives of the curriculum design process to create alignment between the objectives of the learning activities and the student’s real-life experiences. This plan implies the need to connect learning activities with students’ daily lives.

The main advantage of using mathematics, in the current learning design, as the only focus of the investigation is that it provides a nuanced understanding of issues affecting students in the respective subject area. However, the disadvantage associated with this strategy is the failure to understand linkages between students’ poor attitudes towards mathematics and other areas of their lives (Stoet and Geary, 2018). However, creating alignment between educational activities and students’ living experiences will enhance the current curriculum design.

Changes to Theoretical Foundation

Refocusing the motivations for developing the current learning design to include plans for extending group design to align learning strategies with educational materials and students’ leaning outcomes questions the theoretical foundation of the proposed learning design. Subject to this probe, the real-life application of the course’s design theories will be maintained as they are in the proposed plan because no changes are anticipated in the conceptual foundation of the learning program (Sun, Chen and Sun, 2019). As highlighted in the course materials, the current learning design uses pedagogical theory to disseminate learning content.

The learning theory is divided into two categories: behaviorism and constructivism. The behaviorism theory explains attitudinal issues associated with learning and is characterized by the development of a robust reward system for improving performance (Dotger, Dekaney and Coggiola, 2019). The second theoretical foundation for the current learning design is the constructivism theory. It is associated with the development of simulated games and the improvement of collaborative activities in the learning program. Simulated games are linked with problem-solving abilities, while collaborative learning is associated with group activities (Baig, Shuib and Yadegaridehkordi, 2021). Collectively, these actions are accommodated in the institution’s e-learning program. This model of learning has emerged from the evolution of tech-enabled educational design development, which has dominated different processes of curriculum development in the past decade (Wang, Liu, and Zhang, 2018). Therefore, while the educational tools required for making the proposed changes vary, the theoretical foundation for their application should be static to maintain consistency of purpose.

Including New Learner Characteristics

The current educational design for the present learning design is intended to measure students’ engagement levels, mastery of knowledge, ability to work with others, understanding of the banking system, perceptions of money value, improvements in decision-making skills, and enjoyment of class activities. These outcomes are expected to be realized through the effective use of digital tools and recalibration of the learning curriculum to enhance student-teacher engagement (Fleischmann, 2021). The strengths and weaknesses of the proposed design will be highlighted in subsequent sections of this study as well as areas that could be improved in terms of the current functionality and use of digital tools in improving the learning design. However, for purpose of the current investigation, the study will collect additional data from students to implement the new take in lesson design. To recap, the new goal is to extend group design plans to align learning strategies with educational materials and students’ learning outcomes for a comprehensive representation of educational design outcomes. In line with this new focus of curriculum development, students’ experiences with technology will be the first type of new data to be collected in the program.

Students’ Experiences

The current design of the learning program is exclusively focused on promoting the achievement of academic goals without the inclusion of practical applications of students’ experiences beyond the simulated exercises. Including student’s experiences in the service design will improve the learning design by transforming it from being exclusively academic-focused to be more inclusive, through service learning (Bigirwa, Ndawula and Naluwemba, 2020). Service-learning helps to merge academic aspects of learning with students’ civic responsibilities to provide a practical basis for the application of classroom knowledge (Gerholz, Liszt and Klingsieck, 2018). The inclusion of students’ experiences in the learning design will help learners to foster a deeper understanding of their academic content because they will have an opportunity to apply such knowledge in real-world situations (Gerholz, Liszt and Klingsieck, 2018). The simulated learning model, which is a key process of the current learning design, helps to achieve the same goal, except that it creates a make-believe environment where students can apply their skills.

The new learning framework will be more flexible than the current one because it will integrate students’ real-life learning experiences into the educational curriculum. In this regard, it will better accommodate nuanced learning approaches based on the individual skills and capabilities of the learners (Martini, 2020). In other words, including student’s unique experiences in the learning design would help teachers to provide personalized learning skills across different levels of development.

Real-Time Data

The reprioritization of goals for the new learning design may require the collection of real-time data from students. This type of data may include geographical positioning, amount of time logged in for educational sessions, and areas of interest for the students. This information is useful because it will help teachers to obtain real-time data from field experiences about learners’ performance, thereby providing them with a practical basis for comparing their theoretical results with practical feedback.

Real-time student data is set to become one of the main educational platforms to be scaled in the future. The current learning design recognizes this fact and has accommodated digital tools in its learning plan. These instruments of data collection and control could improve students’ learning experiences and support the multimodal design of the current learning curriculum (Chappell et al., 2017). The strategy is supported by extant experiential literature, which affirms the efficacy of such tools in improving learning outcomes (Ebbini, 2021). From this background, the current learning design could be improved by collecting students’ real-time data to enhance student’s overall learning experiences.

Collecting students’ real-time information in the learning program may involve integrating face-to-face learning experiences with studio tutorials to explain how knowledge is implemented in the learning setting. This type of setup will be useful in improving student-teacher engagement and the response of online learning activities based on research evidence, which links learning activities with enhanced educational outcomes (Fleischmann, 2021). The pool of data collected from students’ activities on the learning platform will act as a resource center where educational heads, staff, and teachers can find real-time data to coordinate their functions. This strategy follows a global trend in online education where students are being given control and autonomy in their learning processes (Fleischmann, 2021). The proliferation of new digital learning activities, such as online lectures, discussion board questions, and video sharing platforms are part of this evolution (Endres et al., 2021). Therefore, incorporating students’ real-time data into the current digital infrastructure would improve the effectiveness of the learning design.

The collection of new data may create improvements to design functionality, thereby promoting the flow of ideas and intensity of information exchange across various levels of engagement. Thus, the collection of real-time data from the student’s use of the learning program may improve the quality of engagement and learning that may occur in the learning context (Bigirwa, Ndawula and Naluwemba, 2020). Consequently, it is important to collect real-time data from the students to develop constructive learning designs that address current learning challenges and promote continuous improvement at the same time. The current plan has various strengths, such as its multi-layered nature, which makes it possible for teachers to address issues associated with operating in a multi-constraints context.

Open Design Questions

What Improvements to The Data Collection Process Can Be Expected to Gather Additional Data?

Improvements to digital processes of data collection and management will play a critical role in enhancing the effectiveness of the current learning design. The present design incorporates three types of technologies: the learning management system, simulated games, and online activities. For online activities, log data will be tracked from the LMS and used to measure student performance. This data analysis method has been used to measure student outcomes in the higher education sector (Aljaber, 2018). The goal of using this research plan is to develop post-activity feedback for teachers to use in developing their lesson plans.

What Role Will Stakeholders Play to Support Changes?

There are three main categories of users for the current study plan. They include teachers, school administrators, and GCSE students. These groups of people are the major stakeholders in the education sector (Baig, Shuib and Yadegaridehkordi, 2021). They have played a significant role in developing a nuanced understanding of how e-learning methodologies can function effectively in the real-world context of learning (Baig, Shuib and Yadegaridehkordi, 2021). The scope of engagement among these stakeholders should be expanded to include discussion board meetings between students and teachers. Implementing this strategy will improve the quality of data collection because track logs only provide numerical data without highlighting subjective aspects of engagement. Using discussion board questions to enhance stakeholder engagement would help to bridge this gap (Baig, Shuib and Yadegaridehkordi, 2021). This strategy will be useful in assessing the quality of online engagement and measuring student performance on the learning platform.

Based on the above-mentioned plan, the current learning design has three layers, which make it possible for teachers to control layered activities. They include developing the lesson plan, scheduling weekly homework activities, and operating simulated games. The addition of simulated games in the learning design helps to improve its learning efficacy because it allows teachers to vary conditions for learning and investigate associated outcomes (Fox, Pittaway and Uzuegbunam, 2018). Furthermore, it is possible to speed up simulations in a manner that allows teachers to study learning outcomes over a long period. Implementing this plan means that simulations can be slowed down to help users understand a learning phenomenon more intricately (Chernikova et al., 2020). Given that simulations are designed to imitate real-world scenarios, they pose less risk to the implementation of the overall study design and yet provide invaluable data to teachers. Therefore, the use of simulation methods in the current learning design is one of its positive attributes.

How will Feedback Be Included in the New Plan?

The current design, albeit superior in its adoption of new technology tools, lacks a feedback loop mechanism that would enable teachers to use the information obtained from the simulated exercises to improve their lesson plans. The strategy means that the multi-layered orchestration of the lesson design does not linked from end to end. This is a weakness of the current design and future improvements should strive to link the three points of information control as highlighted in Figure 1 below.

The key difference between the proposed outline of the learning design and the current model is the integration of the three levels of engagement between students and teachers. The current model has a linear makeup that allows learners and teachers to move from one stage of engagement to another. However, there is no link showing how the different stages are related. Figure 1 above fills this design gap, thereby providing room for continuous improvement in the learning process because teachers can use the lessons borrowed from operating simulated games to improve their lesson plans.

Conclusion

The findings highlighted in this paper have highlighted significant strengths and weaknesses associated with implementing the current learning design. It proposes changes to the adoption of digital learning tools and functional design structures to make it more inclusive and effective. Additionally, it is proposed that the educational challenge be expanded to align learning strategies with educational materials and students’ leaning outcomes. The result is a comprehensive representation of educational design outcomes and the goal is to highlight connections in students’ attitudes that affect their performance in key subjects. Consequently, making changes to the learning design will improve its effectiveness and create a holistic understanding of the relationship between educational inputs and learning outcomes.

Reference List

Alan, B., Zengin, F. K. and Kececi, G. (2021) ‘Effects of science, technology, engineering, and mathematics education using algodoo to prospective science teachers’ scientific process and education orientation skills’, Journal of Education, 7(2), pp. 1-10.

Aljaber, A. (2018) ‘E-learning policy in Saudi Arabia: challenges and successes’, Research in Comparative and International Education, 13(1), pp. 176–194.

Baig, M. I., Shuib, L. and Yadegaridehkordi, E. (2021) ‘E-learning adoption in higher education: a review’, Information Development, 6(2), pp. 1-13.

Bigirwa, J. P., Ndawula, S. and Naluwemba, E. F. (2020) ‘E-learning adoption: does the instructional design model matter? An explanatory sequential study on midwifery schools in Uganda’, E-Learning and Digital Media, 17(6), pp. 460–481.

Chappell, P. et al. (2017) ‘Using GPS geo-tagged social media data and geodemographics to investigate social differences: a Twitter pilot study’, Sociological Research Online, 22(3), pp. 38–56.

Chernikova, O. et al. (2020) ‘Simulation-based learning in higher education: a meta-analysis’, Review of Educational Research, 90(4), pp. 499–541.

Dotger, B., Dekaney, E. and Coggiola, J. (2019) ‘In the limelight: utilizing clinical simulations to enhance music teacher education’, Research Studies in Music Education, 41(1), pp. 99–116.

Ebbini, G. W. (2021) ‘Transformative design pedagogy: teaching biophilic design through experiential learning’, Journal of Experiential Education, 3(1), pp. 1-13.

Endres, T. et al. (2021) ‘Improving lifelong learning by fostering students’ learning strategies at university’, Psychology Learning and Teaching, 20(1), pp. 144–160.

Fleischmann, K. (2021) ‘Hands-on versus virtual: reshaping the design classroom with blended learning’, Arts and Humanities in Higher Education, 20(1), pp. 87–112.

Fox, J., Pittaway, L. and Uzuegbunam, I. (2018) ‘Simulations in entrepreneurship education: serious games and learning through play’, Entrepreneurship Education and Pedagogy, 1(1), pp. 61–89.

Gerholz, K. H., Liszt, V. and Klingsieck, K. B. (2018) ‘Effects of learning design patterns in service learning courses’, Active Learning in Higher Education, 19(1), pp. 47–59.

Hill, J. L. et al. (2021) ‘Feeling good and functioning well in mathematics education: exploring students’ conceptions of mathematical well-being and values’, ECNU Review of Education, 4(2), pp. 349–375.

Jain, A. and Kaur, V. (2021) ‘Census mapping in India and role of GIS: a look ahead at census 2021’, Indian Journal of Public Administration, 67(4), pp. 540–558.

Martini, N. (2020) ‘Using GPS and GIS to enrich the walk-along method’, Field Methods, 32(2), pp. 180–192.

Metli, A. and Özcan, O. (2021) ‘Investigating the relationship between International General Certificate of Secondary Education (IGCSE) and International Baccalaureate Diploma Program (IBDP): a correlation and regression analysis in languages, sciences, and mathematics’, International Journal of Educational Reform, 30(2), pp. 163–178.

Philip, T. M. and Gupta, A. (2020) ‘Emerging perspectives on the co-construction of power and learning in the learning sciences, mathematics education, and science education’, Review of Research in Education, 44(1), pp. 195–217.

Stoet, G. and Geary, D. C. (2018) ‘The gender-equality paradox in science, technology, engineering, and mathematics education’, Psychological Science, 29(4), pp. 581–593.

Sun, S., Chen, J. and Sun, J. (2019) ‘Traffic congestion prediction based on GPS trajectory data’, International Journal of Distributed Sensor Networks, 5(3), pp. 1-12.

Wang, Y., Liu, X. and Zhang, Z. (2018) ‘An overview of e-learning in China: history, challenges and opportunities’, Research in Comparative and International Education, 13(1), pp. 195–210.

Zhang, Q. and Seah, W. T. (2021) ‘Thematic issue on values and valuing in mathematics education: revisiting mathematics education from cultural perspectives’, ECNU Review of Education, 4(2), pp. 225–229.