Within classrooms, psychologists and teachers use direct behavior observation methods, systematic behavior observations (SBOs) and direct behavior ratings (DBRs), to gather information about students’ behaviors for the purposes of making decisions related to diagnosis and classroom management or behavioral feedback respectively. Observers use SBOs to document predetermined target behaviors exhibited by one or a few target students with standardized parameters. Teachers use DBRs to track and manage their students’ behaviors, most frequently recording data on all of their students’ desirable and undesirable behavior throughout class while teaching. While SBOs and DBRs are ecologically valid, they are limited by observers’ attentional limits and implicit biases, and DBRs are uniquely limited by teacher resources as they balance teaching with recording behavioral data about many students. Intelligent classroom technologies collect a high volume of data with object reliance on algorithms as opposed to observational judgment, which makes them well suited to address limitations specifically associated with the use of data derived from DBRs. Intelligent classroom technologies include eye gaze tracking methods that document students’ visual fixations and wearable or within‐desk devices that monitor students’ movements and/or vocalizations. These devices have the potential to record myriad behaviors of interest and transmit data in vivo for immediate responses from teachers with high efficiency and reduced reliance on human judgment and error. However, they may be associated with ethnical and/or privacy issues, which are discussed along with suggestions for addressing these challenges.