Even though instructional videos are often used in many areas covering a wide range of studies and applications, the lack of a common approach for the definition and classification of instructional videos results in the use of several different models for these purposes. In order to develop such a common approach, there remains the need to build a structure, through which these videos may be defined and classified. The purpose of this study is to design a scheme for the definition and classification of instructional videos based on the namings and qualifications used in the literature and to examine the usability of this scheme. For this purpose, in the first part of this study; the naming and qualifications used in the literature were determined and gathered in a common framework using the content analysis method. Articles published in the Web of Science between 2008 and 2018 with keywords or titles that contained the phrase "instructional video" were accessed. After that, relevant articles were identified using the document analysis method. The results of the analysis indicated that most articles pertained to videos with features structured around the dimensions of interaction, screen design, sequence, included components (picture, voice, text, etc.), subject/content and connection. In the second stage, verification studies were performed to examine the usability of this framework, a classification scheme was developed based on the aforementioned main dimensions and tested for verification. The created scheme allows for classifying video types based on eight main dimensions of interaction, connection, screen design, sequence, component, image format, instant and subject/content, which were identified in the light of the findings obtained from the study. It is believed that this scheme will make it easier for researchers to identify which videos to use. Despite the potential that disruptive technologies offer for facilitating smart pedagogy, the confusion relating to different definitions and classifications in pedagogical understandings is seen as an obstacle for smart teaching systems. The classification model proposed in this study will provide guidance to smart pedagogy studies in terms of data definition and orientation.