Description:We Claim:

1 A system for scientometric analysis and systematic mapping of education technology research, comprising:
 a data collection module configured to retrieve bibliographic information from digital libraries, citation indexes, and academic repositories;
 a data preprocessing module for cleaning, deduplication, filtering, and normalization of bibliometric records;
 a scientometric analysis module configured to perform citation analysis, co-citation mapping, bibliographic coupling, and keyword clustering;
 a systematic review module implementing protocol-based screening, thematic categorization, and structured coding of literature;
 a visualization module configured to generate research maps, thematic evolution diagrams, and collaboration networks; and
 an analytics dashboard for consolidating results, presenting knowledge structures, and supporting decision-making.

2. The system of claim 1, further comprising a multi-stage workflow including:
 a data input stage for aggregating bibliographic datasets;
 a preprocessing stage for preparing validated datasets;
 an analysis stage for executing scientometric techniques;
 a mapping stage for defining scope and research themes;
 a visualization stage for displaying knowledge structures; and
 a reporting stage for generating systematic review outputs.

3. The system of claim 1, wherein the scientometric analysis module further comprises:
 algorithms for citation frequency and impact analysis;
 network construction tools for author, institution, and journal collaborations; and
 clustering engines for identifying emerging themes and research hotspots.
4. The system of claim 1, wherein the visualization module provides key performance indicators (KPIs) including:
 (a) citation and co-citation networks,
 (b) keyword co-occurrence maps,
 (c) thematic evolution graphs,
 (d) author and institutional productivity metrics, and
 (e) collaboration networks across regions and disciplines.

5. The system of claim 1, further comprising an adaptive feedback loop, wherein:
 newly published bibliographic data is periodically integrated;
 the system recalibrates thematic mappings and citation networks; and
 longitudinal trends are updated to ensure continuous refinement of research
insights.

6. The system of claim 1, wherein the data collection module supports integration with multiple bibliographic databases.

7. A method for scientometric analysis and systematic mapping of education technology research, comprising the steps of:
 collecting bibliographic data,
 preprocessing datasets,
 executing scientometric analysis,
 conducting systematic mapping, and
 visualizing results to generate structured insights.

Dated this 30th Day of September 2025
, Claims:FORM 2
PATENTS ACT, 1970
(39 of 1970)
&
The Patents Rules, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)

1. TITLE OF THE INVENTION

“SYSTEM AND METHOD FOR SCIENTOMETRIC ANALYSIS AND SYSTEMATIC MAPPING OF EDUCATION TECHNOLOGY RESEARCH”

2. APPLICANT(S)

a) Name : SR UNIVERSITY
b) Nationality : INDIAN
c) Address : SR UNIVERSITY, Ananthasagar, Hasanparthy
(PO), Warangal - 506371, Telangana, India.

3. PREAMBLE TO THE DESCRIPTION
COMPLETE
The following specification particularly describes the invention and the manner in which it is to be performed.

FIELD OF THE INVENTION

The present invention relates to the field of educational technology research and information science, and more particularly to systems and methods for scientometric analysis and systematic mapping of research trends, knowledge structures, and emerging themes within the domain of education technology. The invention integrates computational scientometrics, bibliometric data processing, and systematic review methodologies to provide a scalable, reproducible, and data-driven framework for conceptualizing the growth, impact, and future directions of education technology research.

BACKGROUND OF THE INVENTION

The rapid expansion of education technology (EdTech) has resulted in a vast body of research spanning diverse themes such as e-learning platforms, adaptive learning systems, and artificial intelligence in education, virtual and augmented reality applications, digital pedagogy, and online assessment tools. While this research output has grown exponentially over the past two decades, the field remains fragmented and difficult to conceptualize systematically, as studies are distributed across multiple journals, conferences, databases, and disciplinary boundaries.

Traditional approaches to reviewing education technology research such as narrative reviews or selective literature surveys are often limited in scope, transparency, and reproducibility. These methods depend heavily on researcher subjectivity, making it challenging to capture the entire knowledge structure, interdisciplinary linkages, and temporal evolution of research themes. Moreover, manual reviews are time-consuming and resource-intensive, which restricts their scalability in addressing large datasets of publications.

Scientometric methods, which involve the quantitative analysis of bibliographic data, have emerged as powerful tools for identifying research trends, co-citation networks, author collaborations, keyword clusters, and thematic evolution. When combined with systematic review methodologies, scientometric analysis provides a data-driven, objective, and replicable approach for conceptualizing research domains. However, existing scientometric studies in education technology often suffer from:

• Lack of standardized frameworks for integrating systematic review protocols with scientometric analysis.
• Inconsistent data collection and preprocessing methods, leading to incomplete or biased mappings of the field.
• Limited visualization capabilities for presenting knowledge structures in an accessible and actionable manner.
• Absence of adaptive feedback mechanisms that allow continuous updates as new research outputs are published.

As a result, researchers, policymakers, and educators face difficulty in synthesizing evidence, identifying research gaps, and forecasting future directions in education technology. There exists a clear need for a comprehensive, scalable, and automated system that combines scientometric techniques with systematic review approaches to deliver robust, reproducible, and interpretable mappings of the education technology research landscape.

The present invention addresses this need by introducing a system and method for scientometric analysis and systematic mapping of education technology research, offering structured workflows, adaptive data processing, advanced visualization dashboards, and evidence-driven insights.

OBJECTS OF THE INVENTION

The primary objective of the present invention is to provide a system and method for scientometric analysis and systematic mapping of education technology research, enabling researchers, educators, and policymakers to obtain structured, reproducible, and data-driven insights into the field.

Yet another objective of the invention is to integrate scientometric techniques with systematic review methodologies in order to overcome the limitations of conventional narrative or manual reviews.

Yet another objective of the invention is to automate the collection, preprocessing, and analysis of bibliometric data from multiple databases and sources, ensuring comprehensive coverage of education technology research outputs.

Yet another objective of the invention is to provide advanced visualization tools such as co-citation networks, keyword co-occurrence maps, thematic evolution diagrams, and collaboration networks to enhance interpretability and knowledge discovery.

Yet another objective of the invention is to establish an adaptive feedback mechanism that allows continuous updating of scientometric analyses as new publications are released, ensuring the system remains current and relevant.

Yet another objective of the invention is to identify research gaps, thematic clusters, and emerging trends in education technology, thereby supporting evidence-based decision-making and strategic planning.

Yet another objective of the invention is to provide a scalable and modular framework that can be applied across institutions, disciplines, and regions for analyzing education technology research systematically.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the present invention relate to the development and implementation of a comprehensive system and method for scientometric analysis and systematic mapping of education technology research. The invention addresses the limitations of conventional narrative reviews and fragmented scientometric studies by offering a structured, data-driven, and reproducible framework that promotes objective analysis, thematic mapping, and actionable insights into the field of educational technology.

Referring to FIG. 1, the invention begins with the establishment of a modular scientometric framework, consisting of the Data Collection Module, Data Preprocessing Module, Scientometric Analysis Module, Systematic Review Module, Visualization Module, and Analytics Dashboard. This architecture ensures seamless integration of bibliographic data retrieval, processing, advanced scientometric techniques, systematic review protocols, and continuous performance tracking.

As shown in FIG. 2, the workflow progresses through a systematic multi-stage process: (1) Data Input and Collection from bibliographic databases and repositories, (2) Data Preprocessing including cleaning, filtering, and normalization, (3) Scientometric Analysis such as citation patterns, co-citation networks, and keyword clustering, (4) Systematic Mapping to define scope and thematic structures, and (5) Visualization and Reporting for presenting research landscapes and trends. Each stage is scaffolded to ensure reliability, reproducibility, and interpretability of outcomes.

FIG. 3 illustrates the systematic mapping process, which includes Planning, Definition of Scope, Data Extraction, and Data Analysis & Presentation. This component ensures that scientometric findings are aligned with systematic review standards, allowing for methodological rigor while synthesizing large volumes of bibliometric data into structured knowledge.

Turning to FIG. 4, the invention incorporates an integrated performance and mapping model. Data collected from research publications is subjected to author-level metrics, journal and institutional performance indicators, impact and citation analysis, and collaborative mapping (co-authorship and co-citation). The results are consolidated into a systematic review framework, producing review outcomes that confirm the effectiveness, structure, and gaps within the field of educational technology research. The iterative feedback mechanism ensures that the analysis evolves as new research outputs become available.

The system is scalable and adaptable, supporting implementation across diverse contexts such as universities, research organizations, policymaking bodies, and global education databases. It is flexible to variations in data sources, research domains, and institutional requirements, ensuring broad applicability.

Through the integration of automated data collection, advanced scientometric techniques, systematic review protocols, and adaptive feedback mechanisms, the present invention provides a robust methodological and technological solution for overcoming existing challenges in synthesizing education technology research. By delivering accurate mappings, thematic structures, and evidence-based insights, the invention contributes significantly to the advancement, governance, and future direction of educational technology research.

BRIEF SUMMARY OF THE DRAWINGS

The invention will be more clearly understood from the following brief description of the accompanying drawings, which illustrate exemplary embodiments of the present invention and are intended to support the detailed disclosure by highlighting the structural and functional aspects of the proposed system.

FIG. 1 illustrates the Scientometric Framework Overview, outlining the foundational modules of the system. This includes the Data Collection Module, Data Preprocessing Module, Scientometric Analysis Module, Systematic Review Module, Visualization Module, and Analytics Dashboard. Together, these elements establish the baseline architecture for conducting large-scale scientometric and systematic analyses of education technology research.

FIG. 2 shows the Workflow of the Scientometric Analysis Process, detailing the sequential steps of the invention. The stages include Data Input, Preprocessing, Scientometric Analysis (citation and keyword networks), Systematic Mapping, Visualization, and Reporting. The diagram demonstrates the structured flow of operations that ensures reproducibility and accuracy in knowledge mapping.

FIG. 3 depicts the Systematic Mapping Process, which consists of four major phases: Planning, Definition of Scope, Data Extraction, and Data Analysis & Presentation. This figure highlights how the invention integrates systematic review protocols with scientometric techniques to achieve rigorous and transparent research synthesis.

FIG. 4 illustrates the Comprehensive Analysis and Review Cycle, representing the final integration of scientometric outputs with systematic review outcomes. The diagram includes performance indicators such as author and journal metrics, thematic mapping, collaboration networks, and review synthesis. This cycle ensures continuous refinement and empirical validation of the research field structure through adaptive feedback mechanisms.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the present invention relate to the development and implementation of a comprehensive system and method for scientometric analysis and systematic mapping of education technology research. The invention addresses the limitations of conventional reviews and fragmented bibliometric studies by offering a structured, scalable, and data-driven framework that integrates automated data collection, scientometric evaluation, systematic review protocols, and visualization tools to generate reproducible insights into the field of educational technology.

Referring to FIG. 1, the invention begins with the establishment of a modular scientometric framework, comprising:

• Data Collection Module, configured to extract bibliographic information from databases, digital repositories, and citation indexes;
• Data Preprocessing Module, responsible for cleaning, filtering, deduplication, and normalization of records;
• Scientometric Analysis Module, enabling techniques such as citation analysis, co-citation networks, bibliographic coupling, and keyword clustering;
• Systematic Review Module, which applies protocol-driven screening, inclusion/exclusion criteria, and thematic coding;
• Visualization Module, capable of generating network maps, thematic evolution graphs, and collaboration structures; and
• Analytics Dashboard, which consolidates results and provides decision-support for researchers, educators, and policymakers.
• This architecture ensures a holistic, end-to-end framework for analyzing and mapping the education technology research landscape.

As shown in FIG. 2, the workflow progresses through a multi-stage process: (1) Data Input from bibliographic sources, (2) Preprocessing to prepare clean datasets, (3) Scientometric Analysis to identify citation trends, keyword co-occurrence, and thematic clusters, (4) Systematic Mapping to define scope and categorize findings, (5) Visualization for intuitive representation of knowledge structures, and (6) Reporting of actionable insights. This pipeline ensures that the outputs are reliable, transparent, and aligned with research best practices.

FIG. 3 illustrates the systematic mapping process, which operationalizes systematic review protocols into the scientometric pipeline. The process includes Planning, Scope Definition, Data Extraction, and Data Analysis & Presentation. This component ensures methodological rigor by linking scientometric results with systematically defined research questions and objectives, producing comprehensive thematic maps and structured evidence syntheses.

Turning to FIG. 4, the invention incorporates an integrated analysis and review cycle. Here, bibliometric outputs are processed into performance indicators such as author productivity, institutional collaboration, journal impact, and citation strength. These results are further synthesized into systematic review outcomes, identifying thematic gaps, emerging research fronts, and longitudinal trends. An adaptive feedback mechanism ensures that new publications are continuously integrated, refining the analysis and keeping the knowledge mapping current and dynamic.

The system is scalable and adaptable, supporting deployment across universities, research centers, policy think tanks, and international organizations. It can be configured for varying dataset sizes, regional focuses, and thematic domains within education technology, making it universally applicable.

Through the integration of automated bibliometric data handling, scientometric techniques, systematic mapping protocols, and visualization-driven reporting, the present invention provides a robust, empirically validated, and future-ready solution for conceptualizing, synthesizing, and advancing education technology research. By enabling accurate and reproducible mapping of knowledge structures, the invention supports evidence-based decision-making, strategic research planning, and the identification of emerging trends and gaps in the educational technology landscape.