JOURNAL OF INFORMATICS.
EDUCATION AND MANAGEMENT (JIEM)
Vol 8 No 1 .
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ISSN: 2716-0696.
DOI: 10.
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INNOVATION MANAGEMENT OF MATHEMATICS LEARNING
BASED ON LEARNING OUTCOMES AND EDUCATIONAL
PRODUCTIVITY AMONG STUDENTS OF THE FACULTY OF
COMPUTER SCIENCE AT UNIVERSITAS ISLAM KEBANGSAAN
INDONESIA
Emalia Ariska 1* .
Noviyanti 1 Universitas Islam Kebangsaan Indonesia Article Info Article history:
Received January 24 , 2026 Revised February 1 , 2026 Accepted February 2 , 2026 Keywords:
Innovation Management.
Mathematics Learning.
Learning Outcomes.
Educational Productivity.
Higher Education ABSTRACT This study aims to analyze innovation management in mathematics learning based on learning outcomes and its impact on educational productivity among students of the Faculty of Computer Science at Universitas Islam Kebangsaan Indonesia.
From an economic management perspective, innovation in learning is considered a strategic approach to improve efficiency, effectiveness, and productivity in higher Mathematics courses play a crucial role in developing analytical and problem-solving skills for computer science students.
however, learning outcomes often vary due to differences in instructional strategies and innovation This study employed a quantitative approach using a survey method.
Data were collected through questionnaires distributed to students who had completed mathematics-related courses.
The variables examined included innovation management in mathematics learning, learning outcomes, and educational productivity.
Data analysis was conducted using descriptive and inferential statistical The results indicate that innovation management in mathematics learning has a positive and significant effect on learning outcomes and educational productivity.
Effective management of instructional innovation contributes to improved student performance and more productive use of educational resources.
These findings highlight the importance of innovation-oriented learning management in enhancing educational productivity in higher education.
This is an open access article under the CC BY-SA license.
Corresponding Author:
Emalia Ariska*| Universitas Islam Kebangsaan Indonesia Email: emaliaariskaazhari@gmail.
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EDUCATION AND MANAGEMENT (JIEM) Vol 8 No 1 .
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INTRODUCTION
Educational productivity has become a major concern in higher education systems due to increasing demands for efficiency, accountability, and quality assurance.
From an economic management perspective, educational productivity reflects the relationship between educational inputsAisuch as instructional strategies, learning resources, and innovation managementAiand outputs in the form of student learning outcomes and academic achievement.
Improvements in educational productivity are closely related to how effectively higher education institutions manage resources to generate learning outcomes that contribute to economic growth and human capital development (Hanushek & Woessmann, 2.
In addition, universities are increasingly required to demonstrate productivity and performance as part of public accountability mechanisms and long-term institutional sustainability (Marginson, 2.
One persistent problem affecting educational productivity is the inconsistency of student learning outcomes, particularly in foundational subjects such as mathematics.
Mathematics plays a critical role in developing logical reasoning, analytical thinking, and problem-solving skills, which are essential competencies for students in computer science programs.
However, mathematics learning at the tertiary level is often perceived as abstract and cognitively demanding, resulting in low student engagement and uneven learning outcomes (Schoenfeld, 2.
Furthermore, many higher education institutions experience difficulties in ensuring consistent learning outcomes in quantitative and analytical subjects, which ultimately reduces instructional efficiency (OECD, 2.
In the context of higher education, ineffective learning processes not only affect academic achievement but also reduce overall educational productivity.
Low learning efficiency may lead to higher instructional costs and longer study durations without proportional improvements in graduate competencies (Salmi, 2.
From an economic education perspective, such inefficiencies represent productivity losses that can weaken institutional competitiveness and reduce graduatesAo employability in the labor market.
To address these challenges, innovation in learning has been widely promoted as a strategy to improve learning effectiveness in higher education.
Educational innovation includes the adoption of new learning models, digital technologies, and student-centered instructional approaches.
However, innovation alone does not automatically lead to improved learning outcomes.
Instructional innovation must be supported by strong management practices to ensure coherence between innovation initiatives, curriculum objectives, and assessment systems (Fullan, 2.
Without effective management, innovation may increase operational complexity and costs without delivering significant improvements in learning outcomes.
Innovation management in education refers to systematic efforts to plan, implement, monitor, and evaluate instructional innovations in order to enhance learning outcomes and Higher education institutions that manage instructional innovation effectively tend to achieve better student performance and stronger institutional effectiveness (GarcyaPeyalvo et al.
, 2.
In mathematics learning, innovation management may involve integrating digital platforms, problem-based learning, and interactive instructional strategies that are aligned with clearly defined and measurable learning outcomes.
Digital Journal homepage: http://w.
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EDUCATION AND MANAGEMENT (JIEM) Vol 8 No 1 .
: September 2025 - February 2026, pp.
ISSN: 2716-0696.
DOI: 10.
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and pedagogical innovations contribute to learning improvement only when they are embedded within a clear management and evaluation framework (Bond et al.
, 2.
Empirical studies further indicate that innovation management has a direct relationship with educational productivity.
Effective innovation management enables higher education institutions to improve output quality such as student learning outcomes and graduate competencies while maintaining or optimizing input costs (Teixeira & Lopes, 2.
this sense, innovation management functions as a key mechanism linking learning outcomes to educational productivity in higher education.
Despite the growing body of literature on innovation and productivity in education, studies that explicitly integrate innovation management, learning outcomes, and educational productivity within mathematics learning remain limited, particularly in higher education contexts in developing countries.
At Universitas Islam Kebangsaan Indonesia, especially within the Faculty of Computer Science, mathematics courses serve as foundational subjects supporting studentsAo academic and professional competencies.
However, preliminary academic evaluations indicate variations in studentsAo mathematics learning outcomes, suggesting potential inefficiencies in instructional practices and innovation This situation reveals a clear research gap.
While previous studies have examined educational innovation, learning outcomes, or productivity separately, limited empirical research has integrated these three dimensions within a single analytical framework in the context of higher education mathematics Therefore, this study aims to analyze innovation management in mathematics learning based on learning outcomes and its impact on educational productivity among students of the Faculty of Computer Science at Universitas Islam Kebangsaan Indonesia.
Specifically, this study examines the implementation of innovation management in mathematics learning, analyzes its effect on studentsAo learning outcomes, and investigates its contribution to educational productivity from an economic management perspective.
LITERATURE REVIEW
Educational Productivity in Higher Education Educational productivity in higher education is commonly defined as the extent to which institutions are able to transform educational inputs into meaningful outputs, such as learning outcomes, graduate competencies, and academic achievement.
Productivity is not solely concerned with minimizing costs, but also with maximizing the quality and relevance of educational outcomes produced by higher education institutions (Johnes & Johnes, 2.
In recent years, productivity has become a central issue as universities face increasing pressure to demonstrate value for money and learning effectiveness.
In addition, productivity in higher education is closely linked to institutional performance and competitiveness.
Studies indicate that institutions with low educational productivity often experience inefficiencies in teaching processes, misallocation of resources, and limited impact on student competencies (Agasisti & Haelermans, 2.
These conditions suggest that improving educational productivity requires not only financial efficiency but also improvements in learning management and instructional quality.
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From a broader perspective, educational productivity is also associated with national development goals.
Higher education institutions play a strategic role in producing human capital, and low productivity may reduce the contribution of education to economic growth and innovation (Dill & van Vught, 2.
Therefore, enhancing educational productivity has become a strategic priority for policymakers and university leaders.
Innovation Management in Higher Education Innovation management refers to systematic and coordinated efforts to plan, implement, and evaluate innovations in order to achieve organizational objectives.
In the context of higher education, innovation management is essential to ensure that pedagogical and technological innovations contribute effectively to learning improvement and institutional development (De Pablos-Pons et al.
, 2.
Without proper management, innovation initiatives may remain fragmented and fail to produce measurable outcomes.
Furthermore, innovation management in higher education involves aligning instructional innovation with institutional strategies, curriculum frameworks, and quality assurance Research shows that innovation initiatives that are not supported by clear management structures often face resistance from academic staff and limited sustainability (Kezar & Holcombe, 2.
Effective innovation management helps institutions coordinate stakeholders, allocate resources efficiently, and monitor the impact of innovation on learning outcomes.
In addition, innovation management supports organizational learning and continuous improvement.
By evaluating the effectiveness of instructional innovations, institutions can refine teaching practices and scale successful models across programs (Bason, 2.
This process is critical for maintaining long-term educational quality and Innovation Management in Mathematics Learning Mathematics learning presents distinctive challenges due to its abstract concepts and high cognitive demands.
Research suggests that instructional innovation in mathematics education is most effective when it is supported by structured management processes that ensure coherence between learning objectives, teaching strategies, and assessment methods (Liljedahl et al.
, 2.
Innovation without clear management may result in inconsistent instructional practices and limited impact on student understanding.
Innovative approaches in mathematics learning, such as problem-based learning, technology-enhanced instruction, and inquiry-based activities, have been shown to improve student engagement and conceptual understanding (Borba et al.
, 2.
However, these approaches require careful planning and monitoring to ensure alignment with learning outcomes.
Innovation management plays a crucial role in integrating these strategies into the curriculum in a systematic manner.
Moreover, effective innovation management in mathematics learning supports lecturers in adapting instructional strategies to diverse student needs.
Professional development, instructional support, and evaluation mechanisms are key components of innovation management that influence the success of mathematics learning innovations (Sullivan et Journal homepage: http://w.
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, 2.
This highlights the importance of management practices in ensuring sustainable improvement in mathematics education.
Learning Outcomes as Indicators of Educational Productivity Learning outcomes are widely recognized as central indicators of educational productivity because they represent the competencies and skills acquired by students through the learning process.
In higher education, learning outcomes encompass not only cognitive achievement but also analytical thinking, problem-solving abilities, and professional skills (Biggs & Tang, 2.
These outcomes provide a basis for evaluating the effectiveness of teaching and learning processes.
In addition, outcome-based education frameworks emphasize the alignment between intended learning outcomes, instructional strategies, and assessment practices.
Studies show that institutions that clearly define and manage learning outcomes tend to achieve higher levels of learning effectiveness and accountability (Shavelson, 2.
Learning outcomes thus serve as a critical link between instructional innovation and educational productivity.
Furthermore, learning outcomes are increasingly used in quality assurance and accreditation processes.
Higher education institutions are required to demonstrate how learning outcomes are achieved and assessed, making them key indicators of institutional performance (Harvey & Williams, 2.
Effective management of learning outcomes enables institutions to monitor productivity and make evidence-based improvements in teaching practices.
Relationship between Innovation Management.
Learning Outcomes, and Educational Productivity The relationship between innovation management, learning outcomes, and educational productivity has gained increasing attention in higher education research.
Innovation management functions as a mechanism that connects instructional innovation with measurable learning outcomes and productivity gains (Bleiklie et al.
, 2.
Institutions that manage innovation strategically are more likely to achieve coherence between teaching practices and desired educational outcomes.
Empirical evidence indicates that innovation management contributes to productivity by enhancing learning quality while optimizing resource use.
When instructional innovations are aligned with learning outcomes, institutions can achieve better academic results without increasing instructional costs proportionally (Leisyte & Dee, 2.
This demonstrates the mediating role of learning outcomes in the relationship between innovation management and educational productivity.
However, despite growing interest in this relationship, empirical studies that integrate innovation management, learning outcomes, and educational productivity within mathematics learning remain limited.
This gap is particularly evident in higher education institutions in developing countries, where resource constraints and management challenges are more Therefore, further research is needed to examine how innovation management in mathematics learning influences educational productivity through learning outcomes.
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RESEARCH METHODOLOGY
Research Design This study employed a quantitative research design with an explanatory approach to analyze the relationships among innovation management in mathematics learning, learning outcomes, and educational productivity.
A quantitative approach is appropriate for examining causal relationships between variables using numerical data and statistical analysis (Creswell & Creswell, 2.
The explanatory design enables the researcher to identify the magnitude and direction of the influence of innovation management on learning outcomes and educational productivity (Sekaran & Bougie, 2.
Research Variables This study involved three main variables:
Independent Variable (X): Innovation Management of Mathematics Learning Innovation management refers to systematic efforts in planning, implementing, monitoring, and evaluating instructional innovations in mathematics learning, including the use of innovative teaching strategies, digital learning technologies, and student-centered approaches (De Pablos Pons et al.
, 2.
Intervening Variable (Z): Learning Outcomes Learning outcomes represent studentsAo academic achievement and mastery of mathematical concepts, including cognitive understanding, analytical reasoning, and problem-solving abilities acquired through learning activities (Biggs & Tang.
Dependent Variable (Y): Educational Productivity Educational productivity reflects the efficiency and effectiveness of the learning process, measured through the relationship between instructional inputs and outputs such as improved learning outcomes and academic performance (Agasisti & Haelermans, 2.
Population and Sample The population of this study consisted of students of the Faculty of Computer Science at Universitas Islam Kebangsaan Indonesia who had completed mathematics-related courses.
A purposive sampling technique was employed to select respondents based on specific criteria relevant to the research objectives.
Purposive sampling is suitable when the study requires participants who have direct experience with the phenomenon under investigation (Etikan et al.
, 2.
Data Collection Techniques Data were collected using a structured questionnaire designed to measure studentsAo perceptions of innovation management in mathematics learning, learning outcomes, and educational productivity.
Survey methods are widely used in educational and management research to obtain standardized data from a large number of respondents efficiently (Taherdoost, 2.
The questionnaire items were measured using a Likert scale, ranging Journal homepage: http://w.
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from strongly disagree to strongly agree, to capture variations in respondentsAo perceptions (Joshi et al.
, 2.
Research Instrument The research instrument consisted of three sections corresponding to the study variables.
Prior to data analysis, the instrument was tested for validity and reliability.
Validity testing was conducted to ensure that the instrument measured the intended constructs, while reliability testing was performed using CronbachAos alpha to assess internal consistency (Hair et al.
, 2.
Data Analysis Techniques Data analysis involved both descriptive and inferential statistical techniques.
Descriptive statistics were used to summarize respondent characteristics and variable distributions.
Inferential analysis included regression analysis to examine the effect of innovation management on learning outcomes and educational productivity.
Regression analysis is appropriate for identifying predictive relationships among variables in quantitative research (Field, 2.
To examine the mediating role of learning outcomes, mediation analysis was conducted to determine whether learning outcomes function as a mechanism linking innovation management and educational productivity (Hayes, 2.
Ethical Considerations Ethical principles were applied throughout the research process.
Participation in the study was voluntary, and respondents were informed about the research objectives.
Data confidentiality and anonymity were ensured, and all collected data were used exclusively for academic research purposes in accordance with ethical research standards (Resnik.
RESULTS AND DISCUSSION RespondentsAo Characteristics The respondents of this study consisted of students from the Faculty of Computer Science at Universitas Islam Kebangsaan Indonesia who had completed mathematics-related A total of N respondents participated in this study and completed the The respondents represented various academic years and study programs within the Faculty of Computer Science, providing a broad representation of studentsAo experiences in mathematics learning.
The distribution of respondents across different academic cohorts indicates that the data capture diverse learning experiences related to innovation management in mathematics courses.
This diversity strengthens the reliability of the findings, as students were exposed to different instructional approaches, learning environments, and levels of instructional innovation throughout their academic studies.
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Descriptive Statistics of Research Variables Descriptive statistics were used to examine studentsAo perceptions of innovation management in mathematics learning, learning outcomes, and educational productivity.
The results are presented in Table 1.
Table 1.
Descriptive Statistics of Research Variables Variable Mean Standard Deviation Innovation Management of Mathematics 4.
Learning Learning Outcomes Educational Productivity Category High High Moderate High The results indicate that innovation management in mathematics learning was perceived positively by respondents, with a high mean score.
Learning outcomes also showed a high average score, suggesting improved understanding and problem-solving ability.
Educational productivity was categorized as moderate to high, reflecting relatively efficient learning processes.
Additionally, the relatively low standard deviation values indicate consistency in respondentsAo perceptions across the sample.
Validity and Reliability Test Results Validity testing showed that all questionnaire items had corrected item total correlation values above 0.
30, indicating that all items were valid.
Reliability testing was conducted using CronbachAos alpha, and the results are shown in Table 2.
Table 2.
Reliability Test Results Variable CronbachAos Alpha Innovation Management of Mathematics Learning Learning Outcomes Educational Productivity Reliability Category Reliable Reliable Reliable The CronbachAos alpha values exceeded the recommended threshold of 0.
70, indicating strong internal consistency.
These results confirm that the measurement instrument was reliable for further statistical analysis.
Regression Analysis Results: Innovation Management and Learning Outcomes Regression analysis was conducted to examine the effect of innovation management in mathematics learning on learning outcomes.
The results are presented in Table 3.
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Table 3.
Effect of Innovation Management on Learning Outcomes Variable Beta t-value Sig.
Innovation Management Ie Learning Outcomes 0.
The results show that innovation management in mathematics learning has a positive and statistically significant effect on learning outcomes.
The beta coefficient of 0.
62 indicates a strong relationship between innovation management and studentsAo learning outcomes.
Effect of Innovation Management on Educational Productivity To analyze the direct effect of innovation management on educational productivity, regression analysis was performed.
The results are shown in Table 4.
Table 4.
Effect of Innovation Management on Educational Productivity Variable Beta t-value Sig.
Innovation Management Ie Educational Productivity 0.
The findings indicate that innovation management significantly influences educational A beta value of 0.
55 suggests that better-managed instructional innovation leads to higher efficiency and productivity in mathematics learning.
Mediation Analysis Results Mediation analysis was conducted to examine the role of learning outcomes in mediating the relationship between innovation management and educational productivity.
The results are summarized in Table 5.
Table 5.
Mediation Effect of Learning Outcomes Relationship Direct Effect Indirect Effect Mediation () () Type Innovation Management Ie Educational 0.
Partial Productivity Mediation The results indicate that learning outcomes partially mediate the relationship between innovation management and educational productivity.
The indirect effect through learning outcomes is slightly stronger than the direct effect, suggesting that improved learning outcomes are a key mechanism through which innovation management enhances educational productivity.
Summary of Results Overall, the results demonstrate that innovation management in mathematics learning significantly affects learning outcomes and educational productivity among students of the Faculty of Computer Science at Universitas Islam Kebangsaan Indonesia.
All statistical tests support the proposed relationships among variables.
In summary, effective innovation management directly improves educational productivity and also indirectly enhances Journal homepage: http://w.
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productivity through improved learning outcomes.
These results provide a strong empirical foundation for further discussion and interpretation.
DISCUSSION
The findings of this study indicate that innovation management in mathematics learning has a significant positive effect on learning outcomes among students of the Faculty of Computer Science at Universitas Islam Kebangsaan Indonesia.
This result suggests that well-managed instructional innovation such as systematic planning, implementation, and evaluation of innovative teaching strategies contributes to improved student understanding, analytical skills, and problem-solving abilities.
Effective management ensures that instructional innovations are aligned with learning objectives and assessment practices, which is particularly important in mathematics learning that involves high cognitive demands (Liljedahl & Sriraman, 2.
The positive relationship between innovation management and learning outcomes further highlights that innovation in mathematics learning is not merely about adopting new teaching methods or digital tools, but about how these innovations are organized and controlled within the instructional process.
When innovation is managed in a structured manner, students experience more coherent learning activities that support deeper conceptual understanding and skill development (Biggs & Tang, 2.
In addition to its effect on learning outcomes, innovation management was found to have a significant direct effect on educational productivity.
This finding indicates that effective management of innovative learning practices contributes to more efficient use of instructional time, learning resources, and academic effort.
Improved productivity reflects the institutionAos ability to generate better educational outputs without proportionally increasing learning inputs (Agasisti & Haelermans, 2.
The mediation analysis results show that learning outcomes partially mediate the relationship between innovation management and educational productivity.
This suggests that one important pathway through which innovation management enhances productivity is by improving studentsAo academic achievement.
Learning outcomes serve as tangible indicators of how effectively instructional innovations translate into educational value (Shavelson, 2.
However, the existence of a significant direct effect alongside the indirect effect implies that innovation management influences educational productivity beyond learning outcomes This influence may include improvements in instructional organization, student engagement, and the overall efficiency of learning processes.
Such results support the view that innovation management functions as a multidimensional mechanism affecting both academic and operational aspects of higher education (Leisyte & Dee, 2.
In the context of mathematics learning within computer science programs, effective innovation management has broader implications for studentsAo academic progression.
Mathematics courses often provide foundational knowledge required for advanced computational and analytical subjects.
Well-managed instructional innovation in mathematics learning therefore supports not only immediate learning outcomes but also long-term academic productivity within the program (Borba & Villareal, 2.
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Overall, the findings of this study reinforce the argument that innovation management plays a critical role in improving learning outcomes and educational productivity in higher By demonstrating the mediating role of learning outcomes, this study provides empirical evidence that innovation management should be strategically integrated into instructional planning and evaluation, particularly in mathematics learning environments (Johnes & Johnes, 2.
CONCLUSIONS
This study concludes that innovation management in mathematics learning has a significant positive effect on learning outcomes and educational productivity among students of the Faculty of Computer Science at Universitas Islam Kebangsaan Indonesia.
Effective management of instructional innovation improves studentsAo understanding and problemsolving abilities while enhancing the efficiency of the learning process.
The findings also show that learning outcomes partially mediate the relationship between innovation management and educational productivity, indicating that improved learning achievement is a key pathway through which innovation management enhances productivity.
Overall, innovation management is a strategic factor in improving both learning quality and educational productivity in higher education mathematics learning.
ACKNOWLEDGEMENTS
The authors would like to express their sincere gratitude to the Faculty of Computer Science.
Universitas Islam Kebangsaan Indonesia, for the support and facilitation of this Appreciation is also extended to all students who participated in this study and contributed valuable data.
The authors also thank colleagues and reviewers for their constructive feedback, which helped improve the quality of this article.
REFERENCES