The Influence of Information Communication Technology (ICT) integration on teaching and learning in South African Schools

Despite recent emphasis on the quality of education for all in South Africa, the department of education still face major challenges that hinder the progress of implementing quality education, especially in the rural areas. Consequently, this study followed an action qualitative method. The overall purpose of the study was to determine the influence of ICT integration in on the quality of teaching and learning in the classroom and to further examine the benefits of using ICT to enhance personal growth, individual performance, critical thinking skills reading and writing skills. The research questions were semi-structured and open-ended. The researcher interviewed nine (9) learners and seven (7) teachers in a two session focus group, first session involved only teachers and last session had only grade 12 learners. The themes of the sessions were documented separately, however, relationship between the themes were identified. The study also performed observation in the classroom to access situations that would have been almost impossible to identify in an interview or a questionnaire. Results shown that a lot still need to be done by the government to initiate the process of integrating ICT in education or empower teachers with ICT skill and to do away with the traditional teaching method. The study however concluded on the positive influence of ICT integration on teaching and learning practices in the classroom for both teachers and learners. Consequently, the study recommends the following: government must provide training and incentives to encourage personal development in teachers and for young graduates to value teaching; policies about lost equipment must be drafted and understood by all parties; deployments of technology innovation, as well, as the imperatives of following the recommendation of UNESCO’s four stages of ICT integratio

Assessment of critical success factors of business process re-engineering in the Nigerian oil and gas industry

Business Process Re-engineering (BPR) is defined as the critical analysis and radical redesign of existing business processes to achieve breakthrough improvements in performance measures like cost, quality, speed, profitability and services. The purpose of this paper is to identify the critical success factors of BPR implementation, to evaluate their effects on the primary measures as expressed by the operational performance and the secondary measures as expressed by the organizational performance, and to find out the effect of the operational performance on the organizational performance of Nigerian oil and gas companies. To achieve these objectives, an empirical study was conducted via the administration of 650 self-administered copies of questionnaire to a randomly selected senior and management staff of eight (8) re-engineered Oil and Gas Companies in Nigeria. Using the framework from Khong & Richardson (2003), factors manifesting operational performance and organizational performance were regressed on the Critical Success Factors (CSFs) manifesting successful BPR. Findings based on the survey revealed that successful BPR can positively affect both operational and organizational performance measures in the Nigerian oil and gas companies

Waste tires steel fiber in concrete: a review

The emergence of waste tire steel fiber (WTSF) which is an undervalued resource was borne out of the need to extract the useful materials in waste tires considering the sheer volume of this resource that is disposed of in landfills globally. These fibers find applications in tunnel linings, hydraulic structures, bridge decks, pavements and slope stabilization. The fiber length has positive influence on compressive strength (increased by more than 10%), flexural strength (increased by more than 50%) and split-tensile strength(increased by more than 30%) while slump and flow (increased by more than 80%) were reduced but can be avoided through careful mixing, reduction of coarse aggregates and utilization of short fibers. Utilization of WTSF contributes to the sustainability of the construction industry. This paper focuses on reviewing the contemporary management of waste tires, fresh and hardened properties of steel fibers extracted from the waste tires, usage of the steel fibers and the durability of concrete containing these fibers

Response Surface Methodology and Statistical Investigation of the Strength of Bituminous Sandcrete Blocks

Spalling is a serviceability related defect in buildings that degrades their appearance and if unchecked, could be a threat to building sustainability and lead to structural failures. It is associated with the effect of moisture on the building especially the blockwall. This research focuses on the production of low water-absorption Sandcrete blocks. The water absorption and compressive strength of blocks using bitumen as a coat and as part of the sandcrete mix are investigated. In assessing the outcome, eight (8) different sets of Sandcrete blocks with varying bitumen contents were defined and nine (9) samples of standard six (6) inches blocks were produced for each set, with three (3) samples per set being tested at 7,14 and 28 days for water absorption and compressive strength respectively. The water sprinkling curing method was used at 24 hours intervals. The results acquired showed that the sets that contained bitumen showed reduced water absorption rates up to 4.06% at 28 days relative to the control samples. The analysis of the experimental result was done using response surface methodology, the percentage of bitumen replacement with sand and curing days was used as the independent variable. Multiple regression equation was obtained to predict investigated properties. Further analysis of the data shows that Sandcrete blocks coated externally with bitumen give the optimum performance in terms of compressive strength and water absorption

Rural Households' Perception of African Yam Bean Utilisation in Ekiti State, Nigeria

This study assessed rural household’s perception of the African Yam Bean (AYB) (Sphenostylis stenocarpa) utilisation in Ekiti state, Nigeria. Specific objectives were to describe socioeconomic characteristics of rural households in the study area; examine the extent of utilisation among rural households; and constraints to utilisation of AYB in the study area. Multistage sampling procedure was used to select one hundred and twenty respondents. Data collected using structured interview schedule were analysed using descriptive statistical techniques and Pearson correlation. The results revealed majority of rural household (67.5%) had favourable perception of African yam bean utilisation, though moderate number of rural households rarely utilising as food, cover crop and fertiliser. Prolonged cooking time, odour during cooking and hardness of the seed coat were the major constraints to its utilisation. Furthermore, there was positive and significant relationships (p < 0.05) between rural households’ socio-economic characteristics such as household size (r= 0. 49), extension contacts (r= 0.38) and rural household perception of utilisation of AYB. It was concluded that rural households have high perception towards utilisation of African yam bean though the utilisation status is declining. Extension personnel should create awareness on the nutritional and health benefits of the crop to alleviate poverty among rural households

Comparison of response surface methodology and hybrid-training approach of artificial neural network in modelling the properties of concrete containing steel fibre extracted from waste tyres

The study presents a comparative approach between Response Surface Methodology (RSM) and hybridized Genetic Algorithm of Artificial Neural Network (GA-ANN) in predicting the water absorption, compressive strength, flexural strength, split tensile strength and slump for steel fibre reinforced concrete. The effects of process variables such as aspect ratio, water–cement ratio and cement content were investigated using the central composite design of response surface methodology. This same experimental design was used in training the hybrid-training approach of artificial neural network. The predicting ability of both methodologies was compared using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Model Predictive Error (MPE) and Absolute Average Deviation (AAD). The response surface methodology model was found more accurate in being able to predict compared to the hybridized genetic algorithm of the artificial neural network. Subjects: Neural Networks; Technology; Concrete & Cement; Waste & Recycling Keywords: Response Surface Methodology; hybrid; genetic algorithm artificial neural network; concrete; flexural strength; steel fibre reinforced concrete; civil engineerin

Performance evaluation of hot mix asphaltic concrete incorporating cow bone ash (CBA) as partial replacement for filler

Given the current realities of incessant pavement distresses frequently experienced on Nigerian highways due to axle loads from heavy-duty vehicles, coupled with the menace of grave environmental pollution from abattoir solid wastes such as Cow-bones, the mechanistic properties of Cow Bone Ash (CBA) as partial replacement for filler in the production of asphaltic concrete via the Marshall Mix Design Method and Artificial Neural Networks (ANN) were investigated in this research. The conventional filler was partially replaced with CBA at 2.5%, 5%, 7.5%, 10%, 20%, 30%, 40% and 50% respectively, in the total mix. Sequel to the production of the bituminous concrete at the various proportions, the samples were submerged in water, in a water bath for 30 minutes at a temperature of 105°C before conducting Marshall Stability and flow tests. Results revealed that the stability and flow of asphaltic concrete containing the CBA were greater than that of the concrete containing the conventional filler. Furthermore, the physical and volumetric properties of the mix also improved as CBA was observed to be finer than the conventional quarry dust, hence reduced the voids present in the mix and stiffened the bitumen film on the aggregate particles. The results obtained further showed that the conventional filler (quarry dust) can be replaced partially with CBA up to 50%. The ANN Model employed was trained and tested by quick propagation (QP) algorithm amongst others such as the Incremental Back Propagation (IBP), Batch Back Propagation (BBP), Levenberg Marquardt (quasi Newton) and genetic algorithm (GA). QP gave the least Root Mean Square Error (RMSE) at the shortest time. The statistical values obtained showed that the ANN model was able to efficiently study and predict the experimental dat

Artificial neural network evaluation of cement-bonded particle board produced from red iron wood (Lophira alata) sawdust and palm kernel shell residues

As a way of promoting environmental sustainability, it becomes paramount to salvage the quantity of agricultural wastes being destroyed or disposed into the environment. A novel strategy to reduce these wastes is by reusing them. In the present study, the physical and mechanical properties of particleboards produced from red iron wood (Lophira alata) sawdust and palm kernel shell (PKS) was evaluated by artificial neural network (ANN). The production of this particle boards involved the synergistic combination of effective parameters such as percentage composition of cement, sawdust and palm kernel shell varied between 25–40, 20–50 and 20–50 respectively. The boards were tested for physical properties such as water absorption (WA), thickness swelling (TS), density and mechanical properties such as modulus of rupture (MOR) and modulus of elasticity (MOE). The networks was trained and tested by Multilayer Normal Feed Forward Perceptron (MNFFP), with a quick propagation learning algorithm. The performance of the ANN network shows it has a high potential for predicting the properties of cement bonded particle board. © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the C