Research on Learning Math

Few question the value of graduating with a college degree in the United States resulting in improved personal, economic, and social outcomes. Yet, many Americans face a major barrier in achieving the mathematical skills necessary to complete most college degrees (Adelman, 2004; Attewell, 2006; Complete College America, 2012). As disturbing, the National Math Advisory Panel (2008) reported 32% of 8th grade students scored at or above proficiency level in mathematics required under No Child Left Behind Act (NCLB) established in 2001 on the National Assessment of Educational Progress examination when only 23% of 12th grade students performed at or above the proficiency level. So, it is not surprising that Complete College America (2012) reports over 50% of students entering community college are placed in remedial courses while close to 20% of four year university students require remediation.

Although controversy continues regarding roles and responsibilities community colleges and universities have for developmental education (Crain, 2001; Oudenhoven, 2002), the number of students placed in remedial courses at four year universities imply this will remain a primary charge for many, if not most, into the future (Bahr, 2008). To encourage universities to take responsibility for developmental education, educational researchers have noted “[remediation] is not an appendage with little connection to the mission of the institution but represents a core function of the higher education community that it has performed for hundreds of years” (Merisotis, 2000; p.79). Although Complete College America challenges K-12 to improve student readiness for college to decrease the need for remediation, Crain (2001) and Bahr (2010) charged higher education with providing effective developmental programs as a moral or ethical responsibility.

As noteworthy, investigators (Adelman, 2004; Attewell, 2006; Bahr, 2010; Complete College America, 2012) have found disproportionality by ethnicity, socio-economic status and English language proficiency in remedial programs in post-secondary education. Students who appear to be most at risk in higher education are the very ones identified in No Child Left Behind (2001) in the K-12 education system. Given these student similarities, Crain (2001) advocated for effective developmental education as paramount from both a pragmatic and social justice perspective to support the most disadvantaged among us similar to reform movements for accountability in K-12 education (i.e., Individuals with Disabilities Education Act, 2004; No Child Left Behind, 2001).

Although early research in remedial education was criticized due to a lack of internal and external validity controls as well as problems with definitions and agreed upon benchmarks, three well designed studies provided valid results regarding its effectiveness (Attewell, 2006; Bahr, 2008; Bettinger & Long, 2004; Boylan & Bonham, 2012). Consistent conclusions from these national data sets indicated economic outcomes for students who “successfully remediate” within a developmental [math] education program in either community college or university are very similar to those students not requiring remediation to attain a college degree. Bahr (2010) demonstrated this was true for all levels of math preparedness. Yet the problem remains, the “successfully remediated” group constitutes only 25% or less of students enrolled in developmental education programs, leaving 75% or more of these college students unable to access the benefits degree completion provides (Bahr, 2010; Complete College America, 2012).

Furthermore, three major influences to improve academic achievement in remedial education were integrated into building our multi-tiered system of supports model to improve student outcomes in higher education when placed in pre-college algebra coursework. First, core constructs from MTSS for K-12 students literature provided the scientifically-based research to address learning needs of at-risk college students (Batsche et al., 2005; Gersten, 2009; Jimerson, Burns, & VanDerHeyden, 2007; Mellard & Johnson, 2008; Pashler et al., 2007; VanDerHeyden & Burns, 2010).

Next, educational psychology research identified a number of student attributes shown to be correlated with academic achievement (Andriessen, Phalet, & Lens, 2006; Bai, Wang, Pan, & Frey, 2009; Bandalos, Yates, & Thorndike-Christ, 1995; Bandura, 1986; Barkoukis, Tsorbatzoudis, Grouios, & Sideridis, 2008; Betz & Hackett, 1993; Boylan, 2009; Brown-Chidsey, 2005; Cassady & Johnson, 2002; Cauley & McMillan, 2010; Cokley, Bernard, Cunningham, & Motoike, 2001; Deci & Ryan, 1985; Dowling, 1978; Fennema & Sherman, 1976; Garavalia & Gredler, 2002; Hustinx, Kuyper, Van der Werf, & Dijkstra, 2009; Ironsmith, Marva, Harju, & Eppler, 2003; Langenfield & Pajares, 1993; Pajares & Miller, 1994; Preckel, Holling, & Vock, 2006; Schloemer & Brenan, 2006; Vallerand, Pelletier, Blais, Briere, Senecal, & Vallieres, 1992; Vizek Vidovic, 1999).

And lastly, K-12 research on student learning contributed effective instructional practices that improve mathematics outcomes (Archer & Hughes, 2011; Deschler et al., 2003; Gersten, 2009; Hollingsworth, & Ybarra, 2008; Loveless, 2011; Marchand-Martella, Slocum, & Martella, 2004; National Mathematics Advisory Panel, 2008; Payzant, & Wolf, 1993; Woodward, Beckmann, Driscoll, Franke, Herzig, Jitendra. Koedinger, & Ogbuehi, 2012).