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Field-Problem Studios for Practice Capacity Development in Agricultural Engineering and Information Technology Professional Master's Education

Author(s)

Xiaoming Fu1, Dongming Zhang1, Zhiqi Li2, XiuquanWan3, Shengxue Zhao1, Wentao Li1

Affiliation(s)

1Heilongjiang Bayi Agricultural University, Daqing, China 2China Grain Reserves Corporation Northern Agricultural Development Co., Ltd, Nenjiang, China 3Beidahuang Group Heilongjiang Hongsebianjiang Farm Co. Ltd., Heihe, China

Abstract

Professional master's education in agricultural engineering and information technology is facing a structural challenge: students are expected to solve open-ended field problems involving machinery, sensing, data, software, management, yet many practice courses remain organized around isolated experiments, short-term placements, and output-based assessment. This study aims to develop a non-linear practice-teaching reform framework that transforms authentic agricultural problems into progressive learning situations and verifiable competency evidence. Drawing on experiential learning, situated learning, work-integrated learning, constructive alignment, and authentic assessment, this paper adopts a design-based reform approach. We propose a Field-Problem Studio and Evidence Portfolio model consisting of five integrated components: problem discovery in agricultural production sites, studio-based technical inquiry, digital evidence capture, external moderation. The model reconstructs practice teaching around the complete process of "field observation-data acquisition-system design-prototype iteration-deployment verification-technical communication". Compared with the traditional practice teaching paradigm, the new teaching mode constructed in this study abandoned the shallow practice training logic with the core of completing the experimental operation and writing the project report, and focused on the four core education dimensions of independent inquiry, iterative optimization design, interdisciplinary knowledge integration .Based on the industry development background of digital agriculture and smart agriculture, this study explores the formation of standardized and landing teaching reform path for the pain point of talent training in application-oriented undergraduate colleges, which can provide important practical reference for colleges and universities to improve the post adaptation ability, scientific and technological innovation ability and comprehensive professional quality of graduates of agriculture related majors.

Keywords

Professional Master's Education; Agricultural Engineering and Information Technology; Practice Teaching; Field-Problem Studio; Competency Evidence; Authentic Assessment; Digital Agriculture

References

[1] Xiao J. Digital transformation in top Chinese universities: An analysis of their 14th five-year development plans (2021-2025). Asian Journal of Distance Education, 2023, 18(2): 186-201. [2] Shulman L S. Signature pedagogies in the professions. Daedalus, 2005, 134(3): 52-59. [3] Dede C. Comparing frameworks for 21st century skills. 21st century skills: Rethinking how students learn, 2010, 20(2010): 51-76. [4] Wolfert S, Ge L, Verdouw C, et al. Big data in smart farming–a review. Agricultural systems, 2017, 153: 69-80. [5] Klerkx L, Jakku E, Labarthe P. A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. NJAS: wageningen journal of life sciences, 2019, 90(1): 1-16. [6] Liakos K G, Busato P, Moshou D, et al. Machine learning in agriculture: A review. Sensors, 2018, 18(8): 2674. [7] Kamilaris A, Prenafeta-Boldú F X. Deep learning in agriculture: A survey. Computers and electronics in agriculture, 2018, 147: 70-90. [8] Kolb D A. Experiential learning: Experience as the source of learning and development. FT press, 2014. [9] Lave J, Wenger E. Situated learning: Legitimate peripheral participation. Cambridge university press, 1991. [10] Billett S. Learning through work: workplace affordances and individual engagement. Journal of workplace learning, 2001, 13(5): 209-214. [11] Billett S. Realising the educational worth of integrating work experiences in higher education. Studies in higher education, 2009, 34(7): 827-843. [12] Biggs J B. Teaching for quality learning at university: what the students does. Open University Press, 2011. [13] Gulikers J T M, Bastiaens T J, Kirschner P A. A five-dimensional framework for authentic assessment. Educational technology research and development, 2004, 52(3): 67-86. [14] Hattie J, Timperley H. The power of feedback. Review of educational research, 2007, 77(1): 81-112. [15] Chen L, Wang C. The role of logic in ideological and political courses in senior high schools: An interpretation of Curriculum Standards 2020, issued by the Ministry of Education of China. Educational Philosophy and Theory, 2023, 55(8): 962-972. [16] Huang Y, Zhang J, Xu Y, et al. College students’ entrepreneurship policy, regional entrepreneurship spirit, and entrepreneurial decision-making. Humanities and Social Sciences Communications, 2024, 11(1): 1-12. [17] Charatsari C, Michailidis A, Lioutas E D, et al. Towards Agricultural Digitalization: Does Higher Agricultural Education Supply Students with Relevant Competencies? //Proceedings. MDPI, 2024, 94(1): 1. [18] Trede F, Macklin R, Bridges D. Professional identity development: a review of the higher education literature. Studies in higher education, 2012, 37(3): 365-384.