Technological Innovation for Sustainable Mobility : Identifying Green Technology Opportunities in the Railway and Automotive Industry through Patent Data Analytics

Yong-Jae Lee 고려대학교 대학원 2024 국내박사

본 연구는 지속가능한 모빌리티를 위한 기술혁신을 목표로 철도 및 자동차 산업의 녹색기술 기회를 파악하기 위한 특허 데이터 분석을 수행한다. 철도 주변압기 기술, 철도 보조 전원 장치 기술, 강화된 유럽 배출가스 기준에 대응하는 친환경 자동차 기술 분야를 중심으로 분석을 수행한다. 첫 번째로, 철도 주변압기 기술 분야의 유망 공백 기술을 도출하고 잠재적인 기술 격차를 탐색하기 위해 특허 분석을 수행한다. 한국, 중국, 일본, 미국, 캐나다, 유럽의 특허청 데이터베이스에서 철도 주변압기 관련 특허 데이터 707개를 수집하였다. 수집된 데이터를 기반으로 특허-IPC 매트릭스를 구축하고 기술 매핑 분석, 시계열 분석, 소셜 네트워크 분석을 수행하여 유망 IPC 세부 기술 영역을 식별했다. 식별된 유망 IPC 세부 기술 영역에 해당하는 특허 데이터를 대상으로 GTM 분석을 수행하여 유망 공백 기술을 도출하였다. 분석 결과, 중국의 CRRC를 중심으로 특허 출원 비중이 증가하고 있으며, 기존 변압기의 냉각 방식인 팬을 제거하고 자연 냉각 방식을 사용하는 '블로워리스(Blowerless) 기술', 기존 변압기에 사용되는 절연유를 없애고 건식 절연 방식을 사용하는 '오일 프리(Oil-Free) 기술', 기존 변압기의 주요 구성 요소인 철심과 권선을 반도체 소자로 대체하는 '솔리드 스테이트(Solid-State) 기술'이 유망한 공백 기술로 식별된다. 이 기술들은 크기와 무게를 줄이고, 에너지 효율을 향상시키며, 소음을 감소시키고, 유지 보수 비용을 절감하는 효과가 있다. 두 번째로, 철도 보조 전원 장치 기술 동향 분석을 통해 기술 분류 체계를 구축하고 유망 기술을 파악한다. 기술과 관련된 특허를 추출하여 기술 분류 체계를 구축하기 위해 LDA 주제 모델링과 N-그램 분석을 통해 기술 주제를 분류하고, 의미를 파악하였다. 이후 시계열 분석과 기술 연관성 분석을 통해 세부 유망 기술 주제를 확인하였다. 마지막으로 특허 출원인의 서지학 및 소셜 네트워크 분석을 통해 유망 기술 주제 분야의 선도 기업과 연구 기관을 확인하였다. 분석 결과, 총 6개의 기술 주제가 확인되었으며, 컨버터(Converter)기술 관련 분야가 세부 유망 기술로 확인된다. 특히 ‘미쓰비시’, ‘히타치’, ‘도시바’ 등 일본 기업들이 이 분야의 R&D를 주도하고 있으며, CRRC를 대표로 하는 중국 기업들도 기술 경쟁력을 강화하고 있다. 추가적으로, 프랑스의 ‘알스톰’은 기술 경쟁력 지표만을 고려할 때 기술 경쟁력이 있다고 평가된다. 세 번째로, 유럽 특허청(EPO)에 출원된 친환경 자동차 기술의 특허 데이터를 분석하여 강화된 유럽 배출가스 기준에 대응하는 글로벌 선도 자동차 기업을 파악하고 기술 기회를 파악하였다. 기술 주제를 파악하기 위해 LDA(Latent Dirichlet Allocation) 기반 토픽 모델링을 사용하였으며, 이를 해석한 N-gram 분석을 통해 기술 기회를 파악하였다. 그리고 글로벌 선도 자동차 기업을 파악하기 위해 기술 매핑 분석을 사용하였다. 분석 결과 기술의 성숙 단계에 해당하는 9개의 기술 주제가 도출되었다. 기술 맵 분석을 통해 파악된 156개의 글로벌 선도 기업 중에는 도요타 자동차, 닛산 자동차, 마쓰다 자동차, 히타치 등의 일본 기업이 다수 포함되어 있다. 자동차 산업은 유럽의 엄격한 환경 규제를 해결하기 위해 수소 연료 전지 자동차, 전기 자동차, 자율 주행 기술 등과 같은 친환경 혁신 기술에 대한 R&D 투자를 더욱 확대할 것으로 예상된다. 마지막으로, 특허 데이터 분석의 한계를 보완하고 결과의 신뢰성을 높이기 위해 최신 학술 논문 및 신문 기사 데이터를 추가적으로 활용했다. 이를 통해 녹색 기술 시장 분석의 정확도와 깊이를 향상시켰다. 나아가, 특허, 논문, 뉴스 데이터 분석 결과와 주요 경제 지표를 PEST (Political, Economic, Social, Technological) 분석 틀에 통합하여 녹색 기술 시장에 영향을 미치는 다양한 요인을 심층적으로 분석했다. 각 데이터 및 경제 지표는 녹색 기술 시장의 기술적, 학문적, 정치적, 경제적, 사회적 측면에 대한 종합적인 정보를 제공했고, 이를 통해 녹색 기술 투자 및 정책 결정에 필요한 핵심 정보를 확보했다. 특히, 저탄소 사회 구축 및 미래 사회의 지속 가능한 발전을 위한 녹색 기술 개발 및 확산 노력은 특허, 논문, 뉴스 데이터 분석 결과에서 공통적으로 확인되어, 현재의 시대적 흐름을 뒷받침했다. 이를 통해 녹색 기술 투자 결정, 정책 수립, 연구 개발 방향 설정뿐만 아니라 녹색 기술 시장의 지속 가능한 성장 전략 수립에도 활용될 수 있었다. 특히, 시장 규모 및 성장률 분석은 녹색 기술 시장의 전반적인 투자 매력도를 평가하는 데 유용했고, 기업 가치 비교 분석은 유망 기업 발굴 및 투자 포트폴리오 구성에 효과적으로 활용될 수 있었다. 추가로, 녹색 기술 시장 분석의 정확도와 깊이를 향상시키기 위한 방안을 모색하고, 철도 및 자동차 산업의 지속 가능한 성장을 위한 녹색 기술 로드맵 수립 및 실행 전략 마련의 중요성을 강조한다. 특히, 지속 가능한 모빌리티를 위한 특허 데이터 분석의 중요성을 부각하며, 특허 데이터가 녹색 기술 시장 분석에 있어 시장 규모, 성장률, 성숙도 등 핵심 정보를 제공함을 밝혔다. 그러나 전통적인 특허 데이터 분석 방법은 특허 공개 지연으로 인해 최신 기술 동향 파악에 어려움이 있으며, 특허 정보 접근 제한 및 분석 도구 부족 등의 문제점이 존재한다. 이에 대한 해결책으로, 미공개 특허 데이터 예측을 위한 AI 기술 도입과 AI 기반 오픈 액세스 (OA) 특허 분석 플랫폼 구축을 제안한다. 더불어, 녹색 기술 관련 지식 공유를 위한 국가 및 기업 간 협력 강화, 개발도상국의 녹색 기술 도입 지원 확대, 지속 가능한 이동성 확보를 위한 국제적 규제 및 기준 마련 등의 필요성을 제기하며, 지속 가능한 모빌리티 구현을 위한 다각적인 노력의 중요성을 강조한다. 본 연구는 특허 데이터 분석을 통해 철도 및 자동차 산업의 기술 동향을 심층적으로 파악하고 미래 녹색 기술 기회를 선제적으로 포착했다. 이러한 연구 결과는 지속 가능한 모빌리티를 위한 연구 개발(R&D) 전략 수립 및 정책 수립에 기여할 뿐만 아니라, 철도 및 자동차 산업의 녹색 기술 개발 및 활용에 중요한 시사점을 제공하여 궁극적으로 지속 가능한 모빌리티 실현에 기여할 것으로 기대된다. In this study, we conduct patent data analytics to identify green technology opportunities in the railway and automotive industry with the aim of technological innovation for sustainable mobility. Our analytics focuses on three specific fields: '(1) Railway Main Transformers', '(2) Railway Static Inverters', and '(3) Eco-Friendly Automotive Technology aligned with Stricter European Emission Standards'. Firstly, we conduct a patent analytics to identify promising vacancy technologies and explore potential technological gaps within the field of railway main transformers technology. Patent data related to railway main transformers technology was collected from patent databases in KIPO (Korea), CNIPA (China), JPO (Japan), USPTO (USA), CIPO (Canada), and EPO (Europe). A total of 707 patent data was collected. Based on the collected data, a patent-IPC (International Patent Classification) matrix was constructed, and further analytics was conducted through technology mapping, time series analytics, and social network analytics. This process aimed to identify promising detailed technology areas within the IPC classification. GTM (Generative Topographic Mapping) analytics was then performed on the patent data corresponding to the identified promising detailed IPC technology areas to derive promising vacancy technologies. As a result of the analytics, an increasing proportion of patent applications were centered on CRRC, a Chinese company. Additionally, promising vacancy technologies were identified, including: "Blowerless technology" which eliminates fans in transformer cooling, "Oil-Free technology" which eliminates insulating oil, and "Solid-State technology" which replaces core components with semiconductors. These technologies offer benefits such as reduced size and weight, improved energy efficiency, lower noise levels, and reduced maintenance costs. Secondly, to identify promising technologies in railway static inverters, we established a technology classification system through patent data analytics and technology trend analytics. Through LDA thematic modeling and N-gram analytics, we classified technology topics and grasped their meaning. Subsequently, time series analytics and technology relevance analytics helped identify detailed promising technology areas. Finally, bibliographic and social network analytics of patent applicants revealed leading companies and research institutes in these promising areas. Our analytics identified a total of 6 technology topics, with converter technology emerging as the most promising area. Notably, Japanese companies like Mitsubishi, Hitachi, and Toshiba are leading R&D efforts, while CRRC from China is also strengthening its technological competitiveness. Additionally, Alstom in France stands out in terms of technological competitiveness based solely on the technology competitiveness index. Thirdly, we analyzed patent data of eco-friendly automotive technology filed with the European Patent Office (EPO) to identify global leading automakers responding to stricter European emission standards and to uncover technology opportunities. LDA (Latent Dirichlet Allocation)-based topic modeling was used to identify technology topics, while N-gram analytics interpreted these topics, and technology life cycle (TLC) analytics helped us identify technology opportunities. Then, technology mapping analytics was employed to identify global leading automakers. The analytics resulted in nine technology topics corresponding to the maturity stage of the technology. Many of the 156 global leading companies identified through technology map analysis are Japanese companies such as Toyota Motor, Nissan Motor, Mazda Motor, and Hitachi. To address stricter environmental regulations in Europe, the automotive industry is expected to further increase R&D investment in eco-friendly innovative technologies like hydrogen fuel cell vehicles, electric vehicles, and autonomous driving technologies. Lastly, the latest academic papers and newspaper articles were incorporated to address the limitations inherent in patent data analysis and enhance the reliability of the results. This approach improved the accuracy and depth of the green technology market analysis. Moreover, a PEST (Political, Economic, Social, Technological) analysis framework was employed, integrating patent, paper, and news data with major economic indicators to comprehensively examine the factors influencing the green technology market. Each data source and indicator provided a multi-faceted view of the technical, academic, political, economic, and social dimensions of the market, yielding crucial information for green technology investment and policy decisions. Notably, the results consistently revealed a commitment to developing and disseminating green technologies for a low-carbon society and sustainable future, aligning with current global priorities. This information could be used not only for investment decisions, policymaking, and R&D direction but also for shaping sustainable growth strategies for the green technology market. Specifically, market size and growth rate analyses were valuable for assessing overall investment attractiveness, while comparative analyses of corporate value could aid in identifying promising companies and constructing investment portfolios. Additionally, this study explores strategies to enhance the accuracy and depth of green technology market analysis and emphasizes the importance of establishing and implementing green technology roadmaps and execution strategies for the sustainable growth of the railway and automotive industries. It highlights the significance of patent data analysis for sustainable mobility, revealing that patent data provides essential information such as market size, growth rate, and maturity in green technology market analysis. However, traditional patent data analysis methods face challenges in identifying the latest technology trends due to delays in patent disclosure, as well as issues such as limited access to patent information and a lack of analysis tools. To address these challenges, the study proposes the introduction of AI technology for predicting undisclosed patent data and the establishment of an AI-based Open Access (OA) patent analysis platform. Furthermore, the study calls for strengthened cooperation between countries and companies to share knowledge related to green technology, expanded support for developing countries to adopt green technology, and the establishment of international regulations and standards to ensure sustainable mobility, emphasizing the importance of multifaceted efforts to achieve sustainable mobility. In this study, we have provided a deep understanding of technology trends in the railway and automotive industries through patent data analysis and has proactively identified future green technology opportunities. These research findings are expected to contribute not only to the establishment of R&D strategies and policies for sustainable mobility but also to provide important implications for the development and utilization of green technology in the railway and automotive industries, ultimately contributing to the realization of sustainable mobility.

Technology-enhanced education reform: An historical analysis of a learning system. The evolution of the Office for Mathematics, Science and Technology Education at the University of Illinois, 1993--2002

Reese, George Clifford University of Illinois at Urbana-Champaign 2002 해외박사(DDOD)

This dissertation presents an historical analysis of the evolution of the programs and activities of the Office for Mathematics, Science and Technology Education (MSTE) at the University of Illinois at Urbana-Champaign (UIUC). MSTE, a unit located in the College of Education, is devoted to the technology-based reform of mathematics and science in grades K through 16. The author uses the model of Donald Schön as a framework to view the development of the Office as the interdependent evolution of theory, structure, and technology. The Office is portrayed as an example in the education community of a “learning organization.” The latter, according to Schön, is “an organization that changes rapidly without intolerable disruptions” (Schön, 1971). Starting as a small office for collecting information on campus-based K–16 activities devoted to mathematics, science, and technology education, MSTE, in less than ten years (1995–2002), evolved into a set of communities and networks of practice that use advanced technologies to further education reform, particularly in mathematics, science, and technology education. The chronology of the MSTE program is presented through a discussion and analysis of its evolving technologies including the many challenges that the Office encountered in working with the World Wide Web and other Internet tools. Office personnel learned first to find resources on the Web and link to them and then, through its own Web server, they made substantial contributions to the interactive courseware content on the Web, including lesson modules, Java applets, programs for download, and online support for the materials on the MSTE site (www.mste.uiuc.edu). In recent years the MSTE site has become very popular, delivering millions of files each month to teachers around the globe. While Schön discussed his model in the context of business and government organizations, MSTE is an example of a learning system in education. In particular, the MSTE program provides a series of lessons learned about the uses and opportunities available in education through the uses of Internet technologies.

A Property-Function based Approach to Patent Mining for Technology Foresight

윤장혁 포항공과대학교 대학원 2011 국내박사

Modern economies emphasize the role of research and development (R&D) that promotes the creation, diffusion and accumulation of intellectual properties within economic systems. Technology foresight allows creating potential and intangible needs of customers by developing value-creating technologies or products for market integration and new market creation. Some previous approaches for technology trend analysis and technology evolution analysis are considered to be useful for technology foresight. However, two points should be complemented for experts to more focus on their knowledge services in that the approaches are relies heavily on knowledge and skills of experts such as domain experts or TRIZ (Russian acronym: the Theory of Inventive Problem Solving) experts, which are unavailable or expensive. They are 1) the dependency on domain experts’ knowledge in analyzing technological trends of emerging or related technology areas, and 2) dependency on TRIZ experts’ skills in identifying technology evolution patterns and their phases from given technologies. As a remedy, this research suggests a property-function based patent mining approach to address the problems. The property addresses ‘what a system is or has’, and expresses a specific characteristic of a system or its sub-systems; the function addresses ‘what a system does or undergoes’, and expresses a useful action of a system or its sub-systems. Properties and functions constitute the abstraction of a system, so they show directions in technological innovations of systems. The property is described mainly using adjectives, and the function is described mainly using verbs. Therefore information concerning properties and functions can be identified from technical information using Natural Language Processing (NLP) because they can be extracted by grammatical analysis. Based on the property-function based approach, this research performs three issues. They are 1) Invention Property-Function Network Analysis of Patents, 2) Mapping Patent Properties and Functions on TRIZ Trends, and 3) An Automated Method for Indentifying TRIZ Trends from Patents. The first issue, ‘Invention Property-Function Network Analysis of Patents’, deals with how to identify trends in technological innovation from new patents. The proposed method automatically extracts properties and function from patent text by exploiting NLP. Using properties and functions as nodes, and co-occurrences as links, an invention property-function network (IPFN) can be generated. The method identifies new technological trends from the IPFN by social network analysis (SNA) indicators including degree, centrality and density. The second issue, ‘Mapping Patent Properties and Functions on TRIZ Trends’, deals with a method to quantify and formalize the processes of TRIZ trend analysis. The TRIZ trend analysis can be used to support the design process and the managerial decision making process to predict further improvements of systems. The third issue, ‘An Automated Method for Identifying TRIZ Trends from Patents’, deals with how to automatically identify TRIZ trends from patents. As a study to facilitate the second issue, the third issue presents a method that consists of 1) extracting properties and functions in the form of binary relation from patent text by exploiting NLP, 2) defining a ‘reasons for jumps’ rule base that arranges trend specific binary relations for TRIZ trend identification, and 3) determining specific trends and trend phases by measuring semantic sentence similarity between binary relations in patents and ones in the rule base. Through these issues, this research provides following contributions: 1) providing methods for systematic identification of trends in technological innovation, 2) facilitating technology foresight for product design and managerial decision making, 3) supporting experts to more concentrate on their knowledge services, and 4) providing a basis for implementing a technology intelligence system.

Technology leadership: How principals, technology coordinators, and technology interact in K--12 schools

Langran, Elizabeth University of Virginia 2006 해외박사(DDOD)

One school division attempted to build technology leadership among principals and technology coordinators in seven schools; this population served as the subjects of this study. The school division's attempt to build technology leadership did not achieve its original project goals, but the participants reported some positive experiences. Results of this study indicated that technology coordinators in this school division have roles that vary greatly across schools. They have an ambiguous role that is problematic when coworkers do not understand the technology coordinator position. Technology coordinators are neither administrators nor classroom teachers, but draw upon experience as former classroom teachers as well as upon a broad skillset for the multiple dimensions of their position. With their access to teachers, principals, and school division administrators, technology coordinators have the potential to act as global change agents and leaders in the schools and help interpret a school division's vision to fit in with the local culture of their school. The principal's role in technology decisions is essential in creating schools that effectively integrate technology. By evaluating teachers' use of technology in the classroom and modeling, these principals created an expectation for technology integration in the classroom. Technology decisions in the school participating in this study were generally initiated from the top, and were often inspired by principals sharing ideas with other principals. Principals and CTIPs participating in this study had varied opinions regarding technology planning. CTIPs and principals who meet frequently are more likely to have similar perceptions of technology planning and policies in place at their school than those who meet infrequently. By building leadership in others, principals and technology coordinators contributed to a distributed leadership model to sustain change despite shifting personnel. Trust emerged as important in increasing risk-taking and the likelihood of innovation implementation while reducing the sense of overload. Technology leadership was defined by the study's participants as encompassing the following characteristics: technology leaders (1) relate and communicate; (2) support and enable teachers to use technology; (3) build leadership in others; and (4) have a clear vision regarding ways in which technology can support learning.

(The) conceptual model of socio-technology analysis and prescriptions for a sustainable society : focusing on the mobile technology case

Baek, Hyun 성균관대학교 기술경영전문대학원 2021 국내박사

As 21st century society has evolved into a technology-centric society, the impact of innovative technologies on society continues to increase. The importance of innovative technologies to society is evidenced by the existence of various analytical methods, study results and actors. When we analyze the impact of technology on society, we often predict its future impact based on how technology has affected past and present trends in society. Analysis on the impact of technology on current trends in society is usually conducted by experts, but users, developers, or citizens might also participate. This study proposes a conceptual model termed ‘Socio-Technology Analysis and Prescriptions’ (STAP) that can be used to analyze the impact of innovative technologies on society and prescribes solutions to any associated problems in order to contribute to a sustainable society. When analyzing the impacts of technology on society, analysts can investigate the effects of technology on society based on a conceptual model developed according to a specific theory. STAP is based on the comprehensive conceptual model from three Science and Technology Studies (STS), these are Technological Determinism (TD), Social Construction of Theory (SCOT), and Actor–Network Theory (ANT). This study adopted not only the perspectives of these three theories that describe the relationship between technology and society, but also takes a critical view of these theories in the process of creating the conceptual model of STAP. In order to implement a draft of STAP, this study extracted and applied keywords to find previous studies which relate to the impact of mobile technology on society using the Systematic Literature Review (SLR) methodology as part of the conceptual model. A prominent feature of the SLR process is its use of natural language processing technology, which is an application of AI technology. In a test case, we successfully analyzed the impact of mobile technology on society through STAP showing it is possible to systematically analyze the impact of technology on society through our conceptual model. The STAP allowed us to identify the underlying causes of major problems and then present solutions. 21세기 사회가 기술 중심 사회로 발전함에 따라 혁신적인 기술이 사회에 미치는 영향은 지속해서 증가하고 있으며, 혁신적인 기술이 사회에 미치는 영향의 중요성은 다양한 분석 방법, 연구 결과 등으로 입증된다. 일반적으로 기술이 사회에 미치는 영향에 대한 분석은 전문가가 수행하지만, 사용자나 개발자 또는 불특정 시민이 참여할 수도 있다. 이 연구는 혁신적인 기술이 사회에 미치는 영향을 분석하고 예측 가능한 문제에 대한 해결책을 제시할 수 있는 '사회-기술 분석 및 처방'(STAP)이라는 개념모델을 제안한다. STAP는 과학 및 기술 연구(STS) 이론 중 세 가지, 기술 결정론 (TD), 기술의 사회 구성 (SCOT) 및 행위자-네트워크 이론 (ANT)을 기반으로 STAP의 개념적 모델을 만들었다. 본 연구는 STAP의 개념적 모델을 적용하기 위해 체계적 문헌 고찰 (Systematic Literature Review) 방법론을 사용하여 모바일 기술이 사회에 미치는 영향과 관련된 64건의 이전 연구 및 미디어 기사들을 대상 문헌으로 선정하였다. 이 문헌들을 분석하여 모바일 기술과 사회의 영향에 관한 키워드들을 추출하였고, 해당 키워드들을 STAP에 적용하여 모바일 기술이 사회에 미치는 영향을 분석하고 해결책을 제시 함으로써 STAP의 적용 가능성을 확인하였다. 이 과정의 중요한 특징 중에 하나는 인공지능 (AI) 기술이 적용된 자연어 처리 기술 (Natural Language Processing)을 사용하여 각 문헌의 핵심 키워드들을 추출하였다. 이 연구는 STAP를 활용하여 모바일 기술이 사회에 미치는 영향을 체계적으로 분석하고, 문제의 근본적인 원인을 식별한 후 해결책을 제시할 수 있었다.

The Impact of IoT on Supply Chain Innovation Performance : Using an Integrated TOE-FVB Framework

GUO MINGYAN 가천대학교 글로벌캠퍼스 일반대학원 2024 국내박사

The arrival of the 5G era is pushing Internet of Things (IoT) technology to the forefront. With the advancements of technology, IoT is rapidly evolving into a ubiquitous global computing network, penetrating various sectors of production and consumption at an astonishing speed. IoT represents significant opportunities for different industries and businesses, particularly for supply chain participants. For supply chain companies, IoT is increasingly changing the way they allocate resources and make operational decisions. Adopting IoT can bring numerous benefits to businesses, but it can also have adverse effects. In this context, the ability of supply chain companies to leverage the technology advantage of IoT and how such technology advantage enhances their supply chain strategic innovation capabilities becomes a topic with both theoretical and practical significance. While IoT technology has immense potential, whether the technology advantage can deliver the expected results for supply chain performance and the mechanisms through which this technology advantage affects supply chain innovation performance (SCIP) still lack a clear answer in the academic world. To address these questions, this study builds a research model on the basis of the technology-organization-environment (TOE) theory, considering the technology advantage of IoT as a technological element, supply chain collaboration (SCC) as an organizational element, and environmental uncertainty as an environmental element to investigate the impact of the technology advantage of IoT on SCIP. Additionally, inspired by the Fit-viability model (FVM), task-technology fit (TTF) and viability are considered as mediating variables to explore their role in the relationship between the technology advantage of IoT and SCIP, aiming to discover the mechanisms through which IoT influences SCIP. Given the widespread application of IoT in the Chinese market, this research focuses on supply chain companies in China that with IoT adoption experience. Through the distribution of survey questionnaires by a professional survey organization, a total of 327 complete questionnaires were obtained. Structural equation modeling is used to analyze the collected data, along with hypothesis testing to derive research conclusions. This study yields eleven main conclusions: the technology advantage of IoT positively impacts TTF, viability, and SCIP respectively; SCC positively impacts TTF, viability, and SCIP respectively; environmental uncertainty negatively impacts TTF, viability, and SCIP respectively; TTF positively impacts SCIP, and viability positively impacts SCIP. The conclusions of this research further expand the theoretical application of both TOE theory and FVM, providing effective recommendations for supply chain companies to better utilize the technology advantage of IoT to enhance SCIP.

테크놀로지 활용 탐구 기반 시민과학 프로그램 참여 학생의 과학 탐구와 사회적 전이 경험

박창미 서울대학교 대학원 2022 국내박사

탐구는 과학 지식의 생성에서 필수적인 활동이며, 과학적 소양을 함양하기 위한 과학교육의 핵심 요소로서 중심적인 역할을 담당한다. 그동안 탐구를 통한 과학적 소양을 함양시키기 위해 다양한 과학교육 연구와 실행 노력이 계속되었다. 탐구와 관련된 다양한 논의들 가운데 학생들이 연구 가치가 있다고 생각하는 문제를 주체적으로 설정하고, 이를 해결하기 위해 과학 지식을 바탕으로 탐구를 설계하고 진행하며, 반성적 사고를 반복하고 공동체 내에서 상호작용을 끊임없이 하는 탐구가 과학교육이 지향해야 할 진정한 탐구의 모습으로 강조되고 있다. 현대사회는 특히 과학기술이 빠르게 발전함에 따라 야기될 수 있는 잠재적 위험 상황이 현실로 다가오면서 과학 지식 및 정보를 바탕으로 합리적 의사 결정을 내릴 수 있는 시민 양성이 점점 중요해 지고 있다. 이러한 흐름 속에서 과학적 소양을 지닌 시민이 자발적인 연구를 통해 과학 기술에 대한 비판적 가치 판단 및 의사 결정과 관련된 활동 등을 활발하게 전개하는 이른바 시민과학 활동이 주목받고 있다. 이러한 시민과학 활동은 다양한 첨단정보기술의 활용으로 참여의 범위와 편의성이 높아지면서 더욱 확대될 것으로 기대하고 있다. 이처럼 최근 시민과학 활동이 활성화 되면서 다양한 시민과학 프로그램이 개발되고 있으며, 그 교육적 목적과 효과가 주목받고 있다. 여러 선행 연구에서는 시민들이 시민과학 프로그램에 참여함으로써 과학에 대한 이해와 실행을 통해 과학적 소양과 시민성을 함양할 수 있었음을 확인하였다. 특히 시민과학 프로그램을 학교에 적용한 연구에서는 학생들이 교실 밖 다양한 학습 사례를 경험하고, 실제적이고 직접적인 과학 활동 기반의 진정한 탐구를 경험할 수 있음을 강조하였다. 한편, 제4차 산업 혁명 시대가 도래하면서 지능정보기술을 기반으로 빠르게 변화하는 시대적 요구를 반영하여 첨단과학기술, 융복합 등 새로운 수요에 대응할 수 있도록 미래형 과학교육 기반 확대의 필요성이 제기되고 있다. 과학교육 종합계획에 따르면 IoT 기반 센서 등을 활용하여 학생들이 자료를 수집하고 이를 온라인 플랫폼에 실시간으로 축적하여 볼 수 있는 과학 탐구 기회를 제공할 예정이라고 하고 있다. 이러한 상황들을 종합해 볼 때 학생들이 테크놀로지를 활용한 진정한 탐구를 할 수 있는 프로그램을 개발하고, 참여 학생들이 유의미한 경험을 하였는지 살펴봄으로써 앞으로의 과학교육의 방향성을 제시할 수 있는 연구가 필요한 시점이라고 하겠다. 따라서 이 연구에서는 ‘테크놀로지 활용 탐구 기반 시민과학 프로그램’을 개발하고 이를 적용하여 참여 학생들의 과학 탐구와 사회적 전이 경험을 분석하였다. 그리고 테크놀로지 활용 과학 탐구와 사회적 전이와의 관계를 파악하고 학생 활동에 주는 영향을 확인하였다. 이를 바탕으로 ‘테크놀로지 활용 탐구 기반 시민과학 활동 모델’을 구성하고 과학적 소양을 갖춘 시민 양성을 위한 과학교육에 시사하는 바를 탐색하고자 하였다. 먼저 교육 프로그램 연구 및 개발 관련 이론에서 제시하는 프로그램 개발 연구에서 필요한 요소들 즉, 프로그램, 실행에 대한 평가, 교육적 목적 구현 여부 확인, 파일럿 적용 등의 과정을 거쳐 ‘테크놀로지 활용 탐구 기반 시민과학 프로그램’을 개발하였다. 그리고 학생들의 경험을 분석하기 위한 이론적 렌즈로서 테크놀로지 활용 과학 탐구(Technology Embedded Scientific Inquiry)와 시민과학 연구 모델인 사회적 전이(transference) 개념을 적용하였다. 각각의 개념에서 도출된 초기 분석틀을 이 연구에서 수집한 데이터를 바탕으로 비교분석법을 통해 수정 및 보완하여 재구조화 하였다. 프로그램 개발을 포함한 연구 기간은 2년이며 2020년 5월부터 프로그램 개발과 1차 파일럿 프로그램 적용이 이루어졌다. 그리고 2021년 4월부터 10월까지 2차 프로그램을 적용하였다. 1차와 2차 프로그램 모두 수도권에 위치한 ‘백학중학교’에서 실시하였으며 그 중 2차 프로그램에 참여한 12명(1학년 4명, 2학년 4명, 3학년 4명)의 학생들의 탐구경험과 사회적 전이를 분석하였다. 개발된 프로그램은 ‘주제 탐색-탐구 수행-사회적 실천-사회적 영향 확인’의 네 단계로 구성되어 있으며, 전반의 두 단계에서는 테크놀로지를 활용한 탐구가 이루어지고 후반의 두 단계에서는 사회적 전이가 이루어지도록 설계하였다. 세부 내용은 시민과학 및 대기환경 문제 소개, 테크놀로지 자원 소개 및 실습, 대기환경 관련 탐구 주제 선정 및 연구계획서 작성, 측정 장치 제작, 과학 탐구 및 사회적 실천, 사회적 영향 확인으로 이루어져 있다. 프로그램을 적용하는 과정에서 학생들의 경험을 분석한 결과, 테크놀로지 활용 과학 탐구 수행 과정에서 학생들은 테크놀로지의 도입으로 과학 조사 과정의 어려움을 극복할 수 있었다. 그리고 과학 의사소통 과정에서 학생들은 교사, 학생, 외부 사람들과의 탐구 전반에 걸쳐 테크놀로지 기반의 활발한 논의를 통해 탐구의 질을 향상시켜갔다. 과학 개념화 과정에서는 테크놀로지를 활용하여 추상적이고 모호한 과학 지식을 감각적이고 실체적으로 이해하고, 관련 지식이나 정보를 탐색하며 확장시켜 나갔다. 이러한 일련의 과정을 통해 학생들은 전형적인 학교 과학 탐구와는 다른 경험을 하는 것으로 나타났다. 자신이 관심있는 생활 주변 주제에 대한 탐구를 수행함으로써 과학에 대한 흥미가 증가하고 테크놀로지의 활용으로 탐구에 대한 신뢰와 자신감이 높아졌다는 것을 확인할 수 있었다. 학생들은 테크놀로지 활용 과학 탐구와 사회적 실천으로 구성된 시민과학 프로그램에 참여하는 과정에서 사회적 전이를 경험하였다. 이들은 자신의 연구에 대한 높은 가치를 부여하면서 스스로 연구를 할 수 있다는 자신감을 바탕으로 가족, 친구들에게 다양한 매체를 통해 연구 성과를 공유함으로써 공유의 효과와 중요성을 인식하였다. 학생이 속한 공동체(가족, 학교 등)의 사람들은 학생의 시민과학 참여 과정에서 보여주는 다양한 모습을 근거로 학생들에게 전문성을 부여하였다. 이렇게 전문성을 부여받은 학생들은 연구와 관련된 질문을 받고 답하는 등 전문가의 역할을 획득하게 되었다. 이를 통해 최종적으로 탐구 주제와 관련하여 타인의 행동 및 태도 변화에 영향을 주거나 타인으로 하여금 시민과학에 관심을 가지는 계기를 마련하는 등 타인의 변화에 영향을 주게 됨으로써 사회적 전이를 경험하였다. ‘테크놀로지 활용 탐구 기반 시민과학 프로그램’에서 테크놀로지 활용 과학 탐구는 직접적으로 탐구가 이루어지는 전반부의 주제 탐색과 탐구 수행 단계에서 학생들이 주제 선정의 폭을 확대하고 탐구를 증진시킬 수 있게 하였다. 또한, 테크놀로지를 활용함으로써 사회적 실천 단계에서 사회적 영향력을 높일 수 있는 포스터를 제작할 수 있었고, 주위 사람들과의 즉각적이고 효율적인 소통이 가능하였다. 그리고 학생들이 주위로부터 탐구에 대한 신뢰를 얻게 되는 근거가 되기도 하였다. 사회적 전이는 사회적 실천을 시작으로 주로 사회적 영향 확인 단계에서 이루어졌다. 이 때 학생들은 사회적 영향 확인 단계 활동이 계기가 되어 사회적 실천, 탐구 수행 단계로 다시 돌아가서 보완을 하거나 탐구 주제를 심화·확장 시켜서 새로운 주제 탐색의 계획을 세우기도 하였다. 뿐만 아니라 사회적 영향을 확인하는 과정에서 개인과 사회가 서로 밀접한 영향을 주고받는다는 것을 경험적으로 깨닫게 되었다. 최종적으로 학생들은 시민과학 활동의 가치를 높게 평가하고 시민과학 활동 확대의 필요성을 강조하기도 하였다. 이러한 학생들의 경험을 종합하여 테크놀로지 활용 과학 탐구와 사회적 전이가 서로 영향을 주어 순환적으로 단계가 이어지는 ‘테크놀로지 활용 탐구 기반 시민과학 활동 모델’을 구성할 수 있었다. 순환적 과정 속에서 학생들은 탐구에 대한 흥미를 바탕으로 탐구 능력을 향상시키고 시민과학자로서의 자긍심과 정체성을 강화해 나갔다. 최근 과학교육의 목표로서 과학적 소양은 과학 지식, 과학적 과정 자체를 습득하는 것에서 머무르지 않고, 삶과 사회와 연결된 과학적 지식의 유용성에 집중하고 나아가 사회 참여, 실천적 행위를 강조하는 것으로 관점이 변화하고 있다. 그리고 이러한 변화는 시민과학이 지향하는 시민의 실천적 과학 소양과 일맥상통한다고 볼 수 있다. 따라서 학생들이 주변에서 쉽게 접할 수 있는 자연현상이나 자신의 삶과 직접적으로 연관되어 있는 과학 이슈 등을 포함한 실제적인 과제들을 탐구하고 이를 바탕으로 행동 및 실천을 함으로써 과학적 소양을 갖춘 시민을 양성하고자 하는 시민과학 프로그램의 개발과 적용이 매우 필요한 시점이라고 할 수 있겠다. 프로그램에 참여한 학생들의 경험을 통해 확인하였듯이, 정확도가 높고 조작이 용이한 테크놀로지를 활용하여 실생활의 문제를 탐구하는 것은 학생들의 과학 탐구 및 과학에 대한 흥미로 이어진다는 점에서 지금까지 학교 수업에서 이루어진 이론 중심적인 탐구의 한계를 극복할 수 있을 것이다. 또한 탐구 결과를 바탕으로 자신의 주장을 공유하면서 주위 사람들의 행동과 태도의 변화에 영향을 주는 사회적 전이 경험은 학생들이 과학 지식 및 정보를 바탕으로 합리적 의사 결정을 내릴 수 있는 시민으로서의 역량을 키울 수 있는 계기가 될 것이다. 그러므로 이를 종합하여 구성된 ‘테크놀로지 활용 탐구 기반 시민과학 활동 모델’은 새로운 과학교육의 방향성을 제시할 수 있을 것으로 기대한다. Inquiry is an essential activity in the generation of scientific knowledge and plays a central role as a key element of science education efforts to cultivate scientific literacy. Science education research has focused on enhancing scientific literacy through scientific inquiry. Specifically, research has emphasized that science inquiry be authentic and aim to support students to connect existing scientific information, to design and engage in inquiry processes, engage in reflective thinking, and interact with the community. These skills are becoming increasingly important in modern society as potentially dangerous situations can arise due to the rapid developments in science and technology which requires the education of citizens who can make rational decisions about dangerous situations based on scientific knowledge and information. In this context, so-called citizen science activities are gaining attention. This refers to citizens with scientific literacy who actively engage in voluntary research activities requiring critical value judgment and decision-making abilities about science and technology. It is expected that citizen science activities will gradually expand in the future by enhancing the scope and convenience of citizens' participation in science activities through the use of various advanced information technology. As such, various citizen science programs are being developed and their educational purposes and effects are attracting attention. Several previous studies confirmed that citizens who participated in citizen science programs were able to cultivate scientific literacy and citizenship by understanding and practicing science. In particular, the application of citizen science programs in schools has emphasized students’ learning experiences outside the classroom and the importance of real inquiry that is based on practical and direct scientific activities. Meanwhile, with the advent of the 4th industrial revolution, the need for future science education expansion is needed to be able to respond to advances in science and technology that reflect rapid changes related to intelligent information technology. According to the 2020-2024 Science education General Plan, students will be able to do scientific inquiry in which they collect data using IoT sensors and send real-time data to online platforms. Considering these circumstances, it is necessary to develop a program that allows students to experience authentic inquiry using technology and to suggest a direction for science education for the future that examines whether participating students had meaningful experiences. The ‘Technology Embedded Scientific Inquiry based Citizen Science Program’ [TESICSP] was developed through a process of program evaluation and implementation, checking whether educational objectives were implemented, and then piloting and further development. The theoretical lens of Transference and TESI, the concept from the Citizen Science Research model and the Technology Embedded Scientific Inquiry, were applied to analyze students' experiences. The initial analysis framework derived from each concept was restructured by modifying and supplementing it through comparative analysis based on the data collected in this study. In addition, the relationship between TESI and transference was explored by examining how experiences affected students’ engagement or attitudes. From this, the study organized the ‘Technology Embedded Scientific Inquiry-based Citizen Science model', which was implemented and evaluated for cultivating citizens with scientific literacy. The research period, including program development, took place over a two-year period. The program development and 1st pilot program implementation started in May 2020. The 2nd program implementation took place from April to October 2021. Both the 1st and 2nd programs were implemented at ‘Baekhak Middle School' located in the Seoul metropolitan area, and the experiences of four first-, second-, and third-graders (n=12) whom all participated in the 2nd program on scientific inquiry and transference were analyzed. The program consisted of four stages: 1) search topics, 2) conduct inquiry, 3) take social action, and 4) find social impacts. TESI took place in the first two stages and transference occurred in the latter two stages. The detailed contents consist of the introduction to citizen science and atmospheric environment issues, introduction and practice with technology resources, selection of research topics related to atmospheric environment and preparation of research plans, production of measurement devices, scientific inquiry and social action, and confirmation of social impact. Analysis of the student experiences in the program revealed that students were able to overcome the difficulties in the process of the scientific investigation by utilizing technology. Through technology embedded scientific communication, students improved the quality of their inquiry activities and actively engaged in technology-based discussions with teachers, students, and others. In the technology embedded scientific conceptualization process, technology was used to understand abstract and ambiguous scientific knowledge more substantively, and to explore and expand related scientific knowledge. Through this series of processes, it was found that students had a different experience from typical school science inquiry. The results demonstrated that by conducting research on everyday life topics of interest to the students that students’ interest in science and their confidence to engage in inquiry increased with the use of technology. While participating in a citizen science program that consisted of scientific inquiry using technology and social action, students experienced transference. Students recognized the effect and importance of sharing their inquiry results through various media with family and friends which increased their confidence that they could conduct research on their own. The people in the community to which these students belong(family, school, etc.) attributed expertise to the students based on the information students gained and shared by participating in the citizen science project. Students acquired the role of experts by answering various questions related to research. This experience resulted in transference as the students influenced changes of others, such as behavior and attitude changes related to the inquiry topics or by providing opportunities for others to also become interested in citizen science. In the ‘search topics’ and ‘conduct inquiry’ stage, where direct inquiry takes place, TESI enabled students to expand the scope of topic selection and to enhance their inquiry. In addition, by using technology, immediate and efficient communication with people around was possible and it was possible to produce posters that could increase social influence at the ‘take social action’ stage. This allowed students to build trust in their research from the members of the surrounding community. Transference, starting with ‘take social action’, was mainly carried out in the stage of ‘find social impacts’. At this time, the activities in the ‘find social impacts’ phase allowed students to return to the ‘take social action’ and ‘conduct inquiry’ stages to supplement, deepen, and expand the research topics which allowed them to establish a new plan for further inquiry. This process of confirming social influence empirically demonstrated that individuals and society closely influence each other. Finally, students highly valued citizen science activities and emphasized the necessity of expanding citizen science activities. By synthesizing the experiences of these students, it was possible to construct a 'technology embedded inquiry-based citizen science model' in which technology embedded scientific inquiry and transference influence each other and cyclically follow steps. In the cyclical process, students improved their inquiry skills based on their interest in inquiry and strengthened their pride and identity as citizen scientists. Recently, science educators have begun to recognize that scientific literacy includes more than acquiring scientific knowledge and engaging in the scientific process itself. Today, the focus is changing to consider the usefulness of scientific knowledge connected to life and society, and the need to emphasize social participation and practical actions. These changes are aligned with the practical aims of improving citizens' scientific literacy. To cultivate citizens who are scientifically literate, it is necessary to develop and implement scientific programs exploring practical tasks, including natural phenomena and scientific issues directly related to their lives, that students can easily engage with and take action. As confirmed through analysis of the experiences of the students who participated in this program, exploring real-life problems using high-accuracy and easy-to-manipulate technology can lead to increases in students' interest in science and inquiry and can help to overcome limitations to engaging in inquiry. In addition, sharing evidenced-based results with community members enables students to experience transference that can influence changes in the behaviors and attitudes of those around them. This can help students to develop their capacity as citizens who can make rational decisions based on scientific knowledge and information. As such, the ‘technology embedded inquiry-based citizen science model' suggests a new direction for science education.

Examining technology fluency: A window into and a reflection of evolving instructor schemas and practices

DeGennaro, Donna University of Pennsylvania 2004 해외박사(DDOD)

Technology proficiency is essential to successful participation in today's society. Few would disagree with this statement. In response to this declaration and coupled with increased concern that youth are technologically unprepared, various technology-focused interventions have arisen. The ultimate goal of these interventions is to create opportunities to engender technology fluency. Researchers currently define technology fluency as learning discrete "skills" and/or having the ability to use computers to create some tangible product. Ensuring participation in a "digital community" accompanies the latter definition. Yet, technology fluency involves something more. Given that technology fosters dynamic, evolving participation in various diversely populated communities, technology fluency also necessitates knowledge of becoming an active contributor to practices in these communities. This dissertation is a qualitative case study of a self-initiated technology-inspired intervention. Specifically, the intervention merges privileged students from a private suburban high school (instructors) with inner-city youth from an impoverished neighborhood (learners) to participate in a web-design course. The question for this research asks how do technology-experienced instructors bridge local understandings of technology learning to successfully engage technology-novice learners? Using a theoretical framework from cultural sociology, this study draws attention to the transformation of instructor schemas and practices as instructors interact with learners throughout the course. The methodology uses design research to examine observation, video, fieldnote and email data. Design research assists in making visible component parts of the environment so that designers can proactively respond to changes that occur during implementation. The intention is not only to illuminate the "what and how" of change, but also offer explanations as to why. This dissertation makes three arguments. First, the relationship between instructor schemas and practices contribute to the structure of the classroom. Next, the ensuing learning environment structure gives way to particular teacher-learner and learner-learner interactions. Finally, the microanalysis of instructor-learner interactions suggests different kinds of individual instructor change. As a result, this research proposes design principles that assist in providing participants with experience in becoming active contributors to practice in technology fluency learning environments. Study of changing schemas and practices during designed program activities bring to light the relationship between theory and practice.

Multimodal Deep Learning-based Decision Support Systems for R&D Performance Profiling

Min-Seung Kim 연세대학교 대학원 2025 국내박사

Technological innovation plays a crucial role in helping firms maintain competitiveness and achieve sustainable growth in today’s fast-paced and increasingly complex global market. Firms are under continuous pressure to innovate, and Research and Development (R&D) activities are at the heart of this process. However, to ensure that these R&D efforts lead to tangible and profitable outcomes, it is essential to evaluate the economic potential of innovations effectively. This dissertation examines the application of multimodal deep learning and graph-based representation learning to develop advanced decision support systems for profiling R&D performance. By leveraging these cutting-edge techniques, this research addresses the need for more accurate and comprehensive methods of assessing R&D outcomes, particularly in relation to technology commercialization. A key focus of this dissertation is the evaluation of the economic value generated by R&D activities and the recommendation of high-potential technologies for commercialization. In contrast to traditional approaches that rely heavily on structured data, this research emphasizes the importance of integrating both structured and unstructured data to capture the full scope of R&D performance. This holistic approach aims to provide firms with more accurate insights into the potential of their innovations, enabling better strategic decision-making. The first study conducts an empirical analysis to identify the key determinants influencing R&D performance, specifically focusing on patent life as a proxy for the effectiveness of R&D activities. By analyzing patent attributes, market conditions, and macroeconomic factors, the study demonstrates how these variables impact the longevity of patents and the broader effectiveness of a firm’s innovation efforts. The second study proposes a multimodal-based R&D performance evaluation model. This model goes beyond conventional evaluation methods by integrating both structured data, such as patent bibliographic information and corporate financial data, unstructured data including textual information from patent documents. By using a multimodal approach, the model captures the complex interactions between a firm’s R&D activities and its financial performance, providing a more accurate and effective assessment of a firm's technological assets. The third study proposes a customized technology recommendation system using graph-based representation learning. Unlike traditional recommendation systems, which often focus solely on patent similarity, this system incorporates firm-specific characteristics to provide more tailored recommendations. By leveraging firm and patent graphs, the system identifies the optimal technologies for commercialization based on the unique characteristics of each firm, such as its industry position, technological expertise, and market needs. This personalized approach ensures that firms receive technology recommendations that align closely with their strategic goals, thus enhancing their ability to successfully commercialize innovative technologies. The findings of this dissertation offer a novel framework for comprehensive R&D performance profiling, emphasizing the strategic importance of patent evaluation and technology recommendation. The proposed models not only enhance the accuracy of economic value assessments but also provide actionable insights for firms seeking to commercialize high-value technologies. These insights enable firms to make more informed decisions regarding their R&D investments, leading to improved innovation outcomes and a stronger competitive position in the market. Ultimately, the findings of this dissertation present a comprehensive framework for R&D performance profiling, emphasizing the importance of strategies for evaluating the economic value of technologies and for effectively integrating external technologies through technology recommendation strategies. The proposed profiling process not only enhances the accuracy of technology assessments but also provides actionable insights that enable firms to commercialize high-value technologies. Furthermore, this dissertation introduces a new approach that integrates advanced deep learning techniques with practical business applications, thereby expanding the knowledge base regarding R&D performance profiling. Based on this, it is expected that this dissertation will contribute to the establishment of a successful decision-making system that integrates both internal and external technological innovations in the development of commercialization strategies for firms. 기술 혁신은 기업이 경쟁력을 유지하고 지속 가능한 성장을 달성하는 데 중요한 역할을 한다. 복잡성이 점차 증대되는 현대의 글로벌 시장에서 기업들은 지속적인 혁신 압박을 받고 있으며, R&D 활동은 이 과정의 핵심에 있다. 그러나 이러한 R&D 노력이 실질적이고 수익성 있는 결과로 이어지도록 하기 위해서는 혁신의 경제적 잠재력을 효과적으로 평가하는 것이 필수적이다. 따라서 본 논문은 멀티모달 딥러닝과 그래프 기반 표현 학습을 적용하여 R&D 성과 프로파일링을 위한 고도화된 의사결정 지원 시스템을 제시하는 것에 목적을 둔다. 이를 통해 본 연구는 기술사업화와 관련된 R&D 성과에 대해 전주기적 관점에서의 정확하고 포괄적인 분석 방법을 제시하고자 한다. 이 논문의 주요 목적은 R&D 활동이 창출하는 기술의 경제적 가치를 평가하고, 사업화에 적합한 높은 잠재력을 가진 기술을 추천하는 데 있다. 전통적인 접근법이 구조화된 데이터에 지나치게 의존하는 것과 달리, 본 연구는 R&D 성과를 분석하는데 있어 비구조화된 데이터와 구조화된 데이터를 통합하는 것에 대한 중요성을 강조한다. 이러한 통합적 접근은 기업의 기술 혁신에 대한 잠재력을 보다 정확하게 통찰하고, 기술사업화 과정에서의 전략적 의사결정을 지원할 수 있도록 한다. 첫 번째 연구에서는 R&D 성과에 영향을 미치는 주요 결정 요인을 식별하기 위한 실증 분석을 수행하며, 특허 수명을 기업의 R&D 성과를 대변하는 대리변수로 적용한다. 이를 통해 특허의 내재적 속성 및 사업화 적용 시장의 업황, 거시경제적 요인이 기업의 R&D 활동에 어떻게 영향을 미치는지 관찰한다. 두 번째 연구에서는 멀티모달 기반의 R&D 성과 평가 모델을 제안한다. 제안 모델은 특허 서지 정보 및 기업 재무데이터와 같은 구조화된 데이터와 특허 텍스트와 같은 비구조화된 데이터를 통합하여 기업의 R&D 성과를 보다 정확하고 신속히 평가할 수 있는 혁신적인 방법론을 제시한다. 세 번째 연구에서는 그래프 기반 표현 학습을 적용한 기업 맞춤형 기술 추천시스템을 제안한다. 전통적인 추천 시스템이 기술의 유사성에만 초점을 맞추는 것과 달리, 제안 시스템은 기업의 고유한 특성 및 과거 기업의 기술사업화 이력을 바탕으로 맞춤형 기술 추천을 제공한다. 이를 위해 제안 시스템은 기업과 특허 그래프에 대한 표현 학습을 적용함으로써 각 기업의 사업화 전략에 최적화된 기술을 식별한다. 최종적으로 본 논문의 연구 결과는 R&D 성과 프로파일링을 위한 포괄적인 프레임워크를 제시하며, 그 중 기술의 경제적 가치를 평가하는 전략과 외부 기술의 효과적 유입을 위한 기술 추천 전략의 중요성을 강조한다. 제안된 프로파일링 프로세스는 기술 평가의 정확성을 향상시킬 뿐만 아니라, 기업이 높은 가치를 지닌 기술을 상용화할 수 있도록 실질적인 통찰을 제공한다. 또한 본 논문은 고급 딥러닝 기법과 실제 비즈니스 응용을 통합한 새로운 접근법을 제시함으로써, R&D 성과 평가와 기술 관리에 대한 지식 체계를 확장하고, 더 나아가 기업이 기술사업화 전략을 수립함에 있어 내외부 기술 혁신을 통합한 성공적인 의사결정 체계를 구축하는데 기여할 것으로 기대된다.

Teachers' Accounts of Successful Technology Integration in Teaching Mathematics

Srisurichan, Rachaya The University of Wisconsin - Madison 2012 해외박사(DDOD)

Technology is promoted as a way to produce a meaningful view of mathematics for students, but to date, there is still no consolidated view of how to appropriately or effectively implement technology in teaching activities. Using a large-scale teacher survey and a multiple-case study of four different mathematics classrooms, this study explores the complex and dynamic nature of teachers' views regarding what it means to successfully use technology in the socially mediated and culturally bound context of the classroom. Results illustrate that features of appropriate and effective technology-based instruction from the teachers' standpoint are interrelated with the nature of their technology use in teaching mathematics, and this interdependent relationship is bound to a multitude of factors associated with their personal characteristics and teaching environments. However, the features for gauging success of technology integration that teachers actually consider in their practice are generally far removed from those proposed in the research paradigm, which reflect broad educational reform goals. Hence, to leverage technology as a medium for engaging with mathematics differently than what students have traditionally experienced, research in the field needs to provide teachers with clearer guidelines for successful technology-based instruction. Some elements, such as the use of technology to provide more access to mathematics, the process of technology-based teaching from teachers' perspectives, interrelationships among factors affecting technology use, and the consideration of technology as a pedagogic cultural artifact, deserve closer scrutiny when developing theoretical constructs for accounts of technology integration. Findings of the study also indicate a need to help teachers develop knowledge needed for fruitful integration of technology, and to offer better teaching conditions in mathematics classrooms. If technology is to find its place in education, we need a clearer, more clarified conceptual foundation and a better support system than what currently exists in the field to move us closer to an articulated research agenda and productive classroom practice.