<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Liile L.  Lekena</style></author><author><style face="normal" font="default" size="100%">Anass  Bayaga</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">KNOWLEDGE GENERATION IN EDUCATIONAL RESEARCH: CASE OF SOUTH AFRICA UNIVERSITIES</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">educational research</style></keyword><keyword><style  face="normal" font="default" size="100%">knowledge generation</style></keyword><keyword><style  face="normal" font="default" size="100%">postgraduate research</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">May/2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://oaji.net/articles/2014/457-1405179843.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">30</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The objective of this study was to investigate forms of knowledge generation in educational research in South Africa in the periods 1995-1999 &amp; 2000-2004. The study was a quantitative by approach. Data from the universities in Gauteng region (South Africa) was extracted from 2340 bound theses database. The results revealed that there are twelve sectors (forms) that have been identified for knowledge generation in educational research.</style></abstract><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">47-60</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anass  Bayaga</style></author><author><style face="normal" font="default" size="100%">Xoliswa  Mtose</style></author><author><style face="normal" font="default" size="100%">Kofi Poku  Quan-Baffour</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SOCIAL INFLUENCES ON THE STUDYING OF MATHEMATICS BY BLACK SOUTH AFRICAN LEARNERS</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">mathematics education</style></keyword><keyword><style  face="normal" font="default" size="100%">social influence</style></keyword><keyword><style  face="normal" font="default" size="100%">South Africa</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">July/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.indexcopernicus.com/search/article?articleId=2594591</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">23</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This study sought to explore how social factors influence learner’s Mathematical development. The respondents were selected according to a mixed method approach, where the dominate approach was quantitative method. The study was undertaken in was one science college in East London. Data analysis was with the aid of both descriptive and inferential statistics. Independent variables for this study were grouped into: (i) characteristics of mathematics achievement (MA) and (ii) characteristics of MA members. Results revealed that the social variables significantly predicted learners’ mathematics achievement. These were status of parent, duration of parental ship, parents’ attendance at school meetings. Other significant predictors included financial and material contributions to learners from parents. </style></abstract><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">30-40</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Anass  Bayaga</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">STATISTICS &amp; PROBABILITY EDUCATION IN SOUTH AFRICA: CONSTRAINTS OF LEARNING</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">mathematics learning</style></keyword><keyword><style  face="normal" font="default" size="100%">South African education</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">April/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://oaji.net/articles/2014/457-1400134002.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">20</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The purpose of this empirical study was to investigate the difficulties of learning statistics and probability amongst students pursuing Postgraduate Certificate of Education (PGCE) programme in University of Fort Hare in South Africa.
 The approach was a mixed method, sampling 43 students, in which case a quantitative analysis (RM-ANOVA, RM-MANOVA &amp; ANCOVA) dominated to test four propositions.
 The findings revealed four conclusions: (1) students receiving deliberate instruction in how to solve problems do become better and are able to ‘think statistically’ (2) there was good reason to suggest that students’ level of specific mathematics skills impact on their statistical ability (3) in contrast, there was not enough supporting evidence to suggest that students’ intuitive notions of probability does get stronger with age and lastly (4) efficacy of computers in guiding design of instruction is an important component of statistical learning.
 Most important implication of the study was that the use of strategies to improve students’ rational number concepts and ratio/proportion reasoning assists to recognise and confront common errors in students' statistical and probability thinking.</style></abstract><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">25-35</style></section></record></records></xml>