Abstract:

Knowledge management (KM) in educational settings is inherently complex because it must integrate heterogeneous information flows across core resources, such as students’ profiles, teachers’ skills, administrative structures, pedagogical approaches, as well as technological infrastructure, in order to enable meaningful sharing of value-added practices that improve decision making. Unlike sectors where knowledge assets are relatively standardized, educational organizations rely heavily on tacit expertise (e.g., instructional judgement, classroom routines, mentoring practices) alongside formal evidence (policies, curricula, assessment records, learning materials) and continuously generated digital traces from learning platforms. Consequently, a key challenge is that educational knowledge is widely distributed, fragmented, and highly context-dependent, that is, what works in one classroom, department, or course cannot be transferred elsewhere without interpretation and adaptation.

Effective KM, therefore, requires mechanisms that:
(a) make tacit knowledge more visible and shareable, and
(b) support common interpretation among stakeholders so that practices can be reused appropriately rather than copied mechanically.

In this paper, we argue that educational decision making can be substantially strengthened by combining KM with Business Intelligence (BI). While KM structures organizational knowledge, BI contributes an analytical layer of sense-making that helps educational organizations move from information accumulation to actionable insight and systematic knowledge dissemination. Methodologically, the paper adopts a conceptual design and a synthetic theoretical analysis of BI as decision support in educational contexts, aiming to articulate how, and under what conditions, BI improves the quality of educational decisions. Particular emphasis is placed on the organizational and ethical prerequisites for responsible implementation, including transparency, interpretability, mitigation of bias, and robust data protection.

More concretely, in this paper we aim to shed light on the scientific fields of KM and BI, as they should be conceived and applied within the ontological network established around the educational decision-making process. In this context, we do not conduct a literature review, a meta-analysis or any other empirical research, but rather seek to build a theoretical framework that describes the relationships among apparently unrelated concepts of the corresponding fields.

Our conceptual paper design involves the following steps:
(1) justifying the choice of KM and BI as the main constructs of the proposed framework,
(2) explicating the role of KM and BI within the framework, and
(3) developing logical arguments about the proposed associations rather than testing them empirically.

Thus, given that few empirical data are available, the paper contributes to extant knowledge by providing a roadmap for understanding educational decision-making by delineating this focal process, how it changes, as well as the factors that may affect it.

Keywords:

Knowledge management, business intelligence, education, decision-making.