Introduction:

Achieving digital transformation is a current challenge in universities and the use of artificial intelligence for academic diagnosis is a step forward in this regard.

Objectives:

To present a strategy for intelligent academic diagnosis that favors personalized attention to the student in the teaching-educational process, using artificial intelligence methods and techniques to achieve a digital transformation in the academic management of the university year group.

Methods:

They are used theoretical and statistical methods, it is assumed structural-functional systemic modeling and they are used attribute selection techniques and artificial intelligence classification algorithms to make the academic diagnosis in a group of students.

Results:

It is exposed lhe logic of intelligent academic diagnosis in the management of the university year group based on the relationships between the process of data acquisition and representation, academic-intelligent prediction and the evaluation of collegiate decision-making, supported by the use of artificial intelligence methods and techniques, to favor the personalized attention of the student and promote the formative sustainability in said management. It is corroborated that with the implementation of the strategy, personalized attention is favored in the teaching-educational process.

Conclusions:

The implementation of the strategy achieves a digital transformation in the academic management of the year group and increases the perception of students about the personalized attention provided by teachers. From the reflective analysis, it is concluded that intelligent academic diagnosis is a new theoretical, necessary and pertinent category for pedagogical studies, since current technological development requires the use of artificial intelligence, hence the importance of its conceptualization.

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