Speaker
Prof. Jun Lin, Xi’an Jiaotong University, China
林军教授，西安交通大学，中国
Research Area: Business Model; Product Management and Innovation; Big Data and Platform Management
研究领域：商业模式; 产品管理与创新； 大数据与平台管理
Title：R&D–Performance Link: The Contingent Effect of Social Networking
Abstract：
While a firm’s investment in research and development (R&D) helps to improve its capability to create value, the economic returns to R&D investments depend on the firm’s value appropriation capability. However, small and medium-sized enterprises (SMEs) lack such capability due to their resource constraints. Building on legitimacy theory and signaling theory, we argue that social networking helps SMEs appropriate value from their R&D investments. Social networking facilitates the dissemination of product information, which reflects the perceptions of customers in general (a source of legitimacy) and signals product quality. The legitimacy and signaling effects improve customers’ evaluations of SMEs and their value offerings, thereby enabling the SMEs to realize benefits from their R&D investments. Thus, we hypothesize a positive moderating effect of social networking on the relationship between SMEs’ R&D and firm performance. We also posit that this moderating effect is stronger for SMEs with less advertising, less analyst coverage, and end-users as their target. Using the panel data of 170 listed Chinese high-technology SMEs from 2011 to 2016, we find general support for our arguments.
A. Prof. William Yeoh, Deakin University, Australia
William Yeoh副教授，迪肯大学，澳大利亚
Research Area: Business intelligence & analytics、Information systems、Crowdsourcing、Cyber security
研究领域：商业智能和分析、信息系统、众包、网络安全
Title：Applying Analytics to Better Understand Students’ Performance and Feedbacks
Abstract：
Dr Yeoh will showcase how advanced analytics can be utilised to enhance students’ performance. Using a large data set acquired from a course offered at an Australian university, the research explores the students’ online quiz completion patterns and the impact of instructional time constraint on online mastery learning. Specifically, utilizing two-phase analytics, the study explores and visualizes students’ online quiz completion patterns and its association with their final examination performance. In addition, Dr Yeoh will also demonstrate how analytics can be applied to better understand students’ feedbacks that are generally collected through a structured survey at the end of a semester as well as through unstructured postings in social media. The presentation will inform educators and university leaders regarding how students’ performance can be enhanced through analytics insights.
A. Prof. Lingling An, Xidian University, China
安玲玲副教授，西安电子科技大学，中国
Research Area: Multimedia Security and Processing, Memory, Learning and Brain-like Computing
研究领域：多媒体安全和处理、记忆、学习和类脑计算
Title：Smart Education Platform of C Language Programming
Abstract：
With the continuous advancement and development of the new model of "AI+education", the teaching concepts of personalized teaching and teaching students in accordance with their aptitude are receiving widespread attention. Driven by the new model, we design and implement a smart education platform for C language teaching, which not only provides a wealth of teaching resources such as syllabus, programming tests, and teaching videos but also adopts the dual-teacher mode of teacher + AI assistant teaching for mixed teaching. First, the platform establishes an initial ability portrait of students and recommends online teacher courses based on their behavior characteristics. Secondly, it tracks the learning process of students throughout the process to form a personalized learning report to assist teachers in personalized guidance. Finally, the platform visualizes the learning data to form individual and class learning effect reports for the improvement of teaching. The teaching data shows that our smart education platform promotes the teaching effects of six teaching classes.
Prof. Xiaohui Zou, Zhuhai Hengqin Searle Technology Co., Ltd. , Sino-American Searle Research Center, China
邹晓辉教授，珠海横琴塞尔科技有限公司，中国
Research Area: Science of language, information and intelligence
研究领域：语言，信息和情报科学
Title：How to steadily improve the teaching quality with human-computer collaboration?
Abstract：
In the existing subject divisions, educational knowledge management technology, knowledge acquisition and management, and knowledge engineering and management belong to three interdisciplinary fields: education science, information management, and service science. The purpose of this research is to adopt the knowledge of large cross-industry, namely: the integration of wisdom, combined with actual needs, to do a series of typical demonstrations. The specific method is: from the standpoint of students and human-computer interaction, from the perspectives of educational knowledge management technology, knowledge acquisition and management, and knowledge engineering and management, respectively, qualitative analysis and quantitative analysis of the three types of ontology of language, knowledge and software analysis. As a result, a series of ambiguity problems encountered in the three aspects of natural language understanding, expert knowledge expression and software pattern recognition are found. Once each is in place, it can be further realized that each can do its best, get what it needs, and get what they want. Its significance lies in: vocational education and the mastery of basic courses, professional basic courses and professional knowledge and skills of universities, middle schools and primary schools can obtain: the comprehensive effect of human-computer interaction, collaboration and coordination, which can significantly and sustainably improve all levels of the teaching quality of various schools is of unique significance for the steady transformation of an educational country into an educational power.