Theory of Academic Productivity by Walberg H. J. (1981) is a rare empirically tested framework for school learning, stems from an extensive review of over 3,000 studies (DiPerna, Volpe, & Stephen, 2002). Wang, Haertel, and Walberg (1997) analyzed 179 handbook chapters and reviews along with 91 research syntheses and surveyed educational researchers to identify the most significant learning influences (Greenberg et al., 2003). They categorized 28 learning influences, finding that eight of the eleven most influential were social-emotional factors: classroom management, parental support, student-teacher interactions, social-behavioral attributes, motivational-effective attributes, peer group, school culture, and classroom climate. Distant factors like state policies or curriculum were less influential. They concluded that psychological determinants of learning are crucial for effective reform (Wang et al., 1997).
Wang et al. emphasized that social, behavioral, motivational, affective, cognitive, and metacognitive characteristics are key variables with the most potential to positively affect student outcomes (DiPerna et al., 2002). Zins et al. (2004) further demonstrated the importance of motivational orientations, self-regulated learning strategies, and social abilities in academic performance. Their findings led to the term “social, emotional, and academic learning” (SEAL), advocating for integrated, long-term educational programming (Greenberg et al., 2003).
Walberg’s model suggests that classroom learning depends on four essential factors—student ability, motivation, quality, and quantity of instruction—and four supplementary factors: the social psychological environment of the classroom, stimulating home conditions, peer group, and media exposure. Each factor is necessary but insufficient alone, requiring all to be at a minimum level for effective learning (Haertel et al., 1983). Walberg et al.’s causal modeling research identified nine productivity factors impacting school learning, noting that some variables (e.g., motivation, prior achievement) have indirect effects (Walberg, Fraser, & Welch, 1986).
Recent findings reinforce that student characteristics (social, behavioral, motivational, affective, cognitive, and metacognitive) have a more significant impact on learning outcomes than state or district-level variables (DiPerna et al., 2002). Wang, Haertel, and Walberg (1993) organized school learning knowledge into major domains and concluded that proximal variables, particularly those related to student characteristics, are more predictive of academic achievement than distal factors like policy and demographics.
