Accelerated Pre Matriculation Mathematics Programs

Accelerated Pre Matriculation Mathematics Programs

For over five decades, accelerated pre-matriculation mathematics programs, often referred to as either “bridge programs” or “boot camps”, have provided an opportunity for enrollees to improve college readiness in a truncated timeframe [1]. Programming within this class has reported substantial positive outcomes, including increased participation in STEM fields amongst underrepresented populations [2] – [4]. http://www.karthividhyalaya.com/ While diverse in their specific form, most programs offer incoming students the opportunity to retake their mathematics placement exam after completing an accelerated period of intensive preparation. This option is particularly valuable for STEM fields, where entering the mathematics portion of the curriculum below calculus is a key predictor of attrition [5], [6]. In spite of the multitude of offerings of such interventions nationwide, limited attention has been devoted in the literature towards their formal assessment [7]. Some results are available, including those provided by Barnett et al., who employed a randomized controlled experiment for students entering eight different two and four year institutions across the state of Texas [8]. Karthi Vidhyalaya Matriculation School Through longitudinal observations over a two-year period, the study concluded that the program had limited impact, with students in the experimental group slightly more likely to pass a collegiate math course within the following year. While assessment using longitudinal outcomes is of value, the clarity of the resulting inference may be distorted based upon confounding factors arising in the period between the intervention and assessment. Additional literature in this area has largely focused on observational studies which analyze the efficacy of bridge programs through comparison of pre and post mathematics placement exam scores. For example, results from both the University of Alabama [8] and Wisconsin [9] have demonstrated substantial increases in the associated placement scores of participants. The latter program leveraged the ALEKS (Assessment and LEarning in Knowledge Spaces) intelligent tutoring software (ITS) during its implementation, and found that comprehension gains were directly related to the time which students spent in the software. The research described herein expands the literature by proposing the assessment of student progression during their participation in accelerated mathematics remediation programming. This assessment is used to develop a dynamic learning model for describing content acquisition during program participation. Such an analysis framework offers value by enhancing analytical insight regarding program policy. For example, understanding such learning dynamics as a function of student characteristics may allow for an optimization of program contact hours or target population characteristics. A limited assessment of the model is provided using data acquired from daily ALEKS learning assessments employed during a one-week mathematics bridge program for intending engineering majors.

A limited assessment of the proposed model was conducted using data gathered from ALEKS learning assessments employed during the one-week Academic Advantage Program (AAP) conducted in 2014 at Wright State University (WSU), a public university located in Dayton, OH, USA. During the program, which has been offered by the College of Engineering and Computer Science for over a decade, students are initially segmented according to their incoming mathematics placement level (which may be determined using either performance on the ALEKS-based placement exam or ACT/SAT score), exposed to intensive classroom instruction over a four-day period, and then permitted to retake their placement exam on the final day of the program. This offering marked the first use of ALEKS software within the AAP program, motivated predominately by its successful inclusion within a preparatory math course offered by the College [10]. In addition to the initial ALEKS assessment conducted for determining baseline comprehension, four additional comprehensive assessments were conducted at the end of each instructional day. The assessment results for each of the students were then fitted according to a least squares quadratic model, corresponding to the assumed linear rate of progression within the review period, with a specified initial value corresponding to the initial assessment results presented in Fig. 2. An inherent assumption in this procedure as it relates the proposed model is that no student reached the saturation point terminating the review period within the four-day intervention.