High Common Factor

1911 ◽  
Vol 3 (4) ◽  
pp. 167-169
Author(s):  
Howard F. Hart
Keyword(s):  
Common Factor ◽  
First Year ◽  
Independent Term ◽  
Number Of Factors ◽  
Degree Term ◽  
Integral Divisor ◽  
The Given ◽  
First Year Student

As the colleges now are requiring highest common factor by factoring methods only, any plan whereby the number of factors to be tried can be lessened is certainly worth while. For in general we must regard as possible any binomial factor whose first-degree term is an integral divisor of the highest term of the given expression and whose independent term is an integral divisor of the independent term of the expression. Thus in such a problem as, “Find the H.C.F. of 5x3 − 21x2 + 5x − 4 and 5x3 − 19x2 + 5x + 4” (McCurdy’s Exercise Book, page 40, example 4) the possible factors that a student might try and must try, unless he were very lucky in those he chose to try first, are x ± 1, x ± 2, x ± 4, 5x ± 1, 5x ± 2, 5x ± 4. And further if the given expressions were, say, cubics having no common binomial factor at all but with a quadratic one instead (e. g., 2x3 + 5x2 + x − 3 and 2x3 − x2 − 5x + 3) I doubt if the ordinary first-year student would get any result unless it were unity.

scholarly journals Performance in grade 12 mathematics and science predicts student nurses’ performance in first year science modules at a university in the Western Cape

Curationis ◽  
2017 ◽  
Vol 40 (1) ◽  
Author(s):  
Katlego D.T. Mthimunye ◽  
Felicity M. Daniels
Keyword(s):  
South Africa ◽  
Academic Performance ◽  
Predictive Validity ◽  
Life Science ◽  
Student Nurses ◽  
First Year ◽  
Western Cape ◽  
Cross Sectional ◽  
Mathematics And Science ◽  
First Year Student

Background: The demand for highly qualified and skilled nurses is increasing in South Africa as well as around the world. Having a background in science can create a significant advantage for students wishing to enrol for an undergraduate nursing qualification because nursing as profession is grounded in scientific evidence.Aim: The aim of this study was to investigate the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules.Method: A quantitative research method using a cross-sectional predictive design was employed in this study. The participants included first year Bachelor of Nursing students enrolled at a university in the Western Cape, South Africa. Descriptive and inferential statistics were performed to analyse the data by using the IBM Statistical Package for Social Sciences versions 24. Descriptive analysis of all variables was performed as well as the Spearman’s rank correlation test to describe the relationship among the study variables. Standard multiple linear regressions analysis was performed to determine the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules.Results: The results of this study showed that grade 12 physical science is not a significant predictor (p > 0.062) of performance in first year science modules. The multiple linear regression revealed that grade 12 mathematics and life science grades explained 37.1% to 38.1% (R2 = 0.381 and adj R2 = 0.371) of the variation in the first year science grade distributions.Conclusion: Based on the results of the study it is evident that performance in grade 12 mathematics (β = 2.997) and life science (β = 3.175) subjects is a significant predictor (p < 0.001) of the performance in first year science modules for student nurses at the university identified for this study.

Model-Eliciting Activities: A Research-Based Method for Inquiry Learning and Professional Development in the Engineering Classroom

2008 ◽  
Author(s):  
Tamara J. Moore
Keyword(s):  
Complex Systems ◽  
Student Development ◽  
Engineering Problem ◽  
First Year ◽  
Foundation Engineering ◽  
Underrepresented Populations ◽  
Model Eliciting Activities ◽  
Engineering Problems ◽  
The Given ◽  
Mathematics And Science

Attracting students to engineering is a challenge. In addition, ABET requires that engineering graduates be able to work on multi-disciplinary teams and apply mathematics and science when solving engineering problems. One manner of integrating teamwork and engineering contexts in a first-year foundation engineering course is through the use of Model-Eliciting Activities (MEAs) — realistic, client-driven problems based on the models and modeling theoretical framework. A Model-Eliciting Activity (MEA) is a real-world client-driven problem. The solution of an MEA requires the use of one or more mathematical or engineering concepts that are unspecified by the problem — students must make new sense of their existing knowledge and understandings to formulate a generalizable mathematical model that can be used by the client to solve the given and similar problems. An MEA creates an environment in which skills beyond mathematical abilities are valued because the focus is not on the use of prescribed equations and algorithms but on the use of a broader spectrum of skills required for effective engineering problem-solving. Carefully constructed MEAs can begin to prepare students to communicate and work effectively in teams; to adopt and adapt conceptual tools; to construct, describe, and explain complex systems; and to cope with complex systems. MEAs provide a learning environment that is tailored to a more diverse population than typical engineering course experiences as they allow students with different backgrounds and values to emerge as talented, and that adapting these types of activities to engineering courses has the potential to go beyond “filling the gaps” to “opening doors” to women and underrepresented populations in engineering. Further, MEAs provide evidence of student development in regards to ABET standards. Through NSF-funded grants, multiple MEAs have been developed and implemented with a MSE-flavored nanotechnology theme. This paper will focus on the content, implementation, and student results of one of these MEAs.

The Impact of On-campus Student Growth on First-year Student Engagement and Success

2007 ◽  
Vol 48 (8) ◽  
pp. 941-966 ◽  
Author(s):  
Steven M. LaNasa ◽  
Elizabeth Olson ◽  
Natalie Alleman
Keyword(s):  
Student Engagement ◽  
Student Growth ◽  
First Year ◽  
The Impact ◽  
First Year Student

scholarly journals 21: THE REACTING TO THE PAST PEDAGOGY AND ENGAGING THE FIRST-YEAR STUDENT

2013 ◽  
Vol 32 (1) ◽  
pp. 351-363
Author(s):  
Paula Kay Lazrus ◽  
Gretchen Kreahling McKay
Keyword(s):  
First Year ◽  
The Past ◽  
First Year Student
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