88 research outputs found
The conventional versus a constructionist Scratch programming and first-year students' achievements in higher education classes: experimental data.
No full textGlobally, learning or teaching the first programming (popularly called CS1) remains a significant educational challenge. Indicators such as CS1 students' engagement, failure and attrition rates, and lack of diversity, continue to show the need for innovating the learning or teaching of novice computer science students. To ease initiating novices to programming, Scratch, a visual programming language, has become a staple of K-12 CS1 classes.
As outcomes of a research project aiming to explore a constructionist Scratch pedagogy with novice CS students in higher education, we present these datasets. In the research lasting two successive academic sessions, we conducted two quasi-experimental studies involving four intact CS1 classes in selected public polytechnic in the north central Nigeria. In each study, we randomly assigned the classes to the experimental and control groups, constituting the constructionist Scratch and the conventional CS1 classes, respectively.
Instruments for collecting data include a student profile questionnaire, a pretest, and posttest. Sequel to ethical clearance and permission from the selected schools, we conducted each study during the first semester of each academic session, in the first seven to eight weeks. During the first to second week, we administered students who consented to take part with the questionnaire and the pretest. Learning or teaching in the two classes lasted six weeks. Then both classes took the posttest. An independent CS educator who is not part of this research marked all the achievement tests, following a rubric prepared by the first author. To strengthen the research design and the possibility of arriving at valid causal evidence, we employed a Coarsened Exact Matching (CEM) algorithm to generate matched samples of experimental and control data, which we used in the analysis.
Data presented here includes the raw, unmatched and matched experimental datasets from both studies. A researcher can make use of the data:
To explore if some background variables not addressed in the original research may moderate CS1 students' achievements. For instance, their prior achievements in mathematics, physics, or English.
To uncover some interesting patterns using machine learning algorithms.
To validate the outcome of the original experiment by using the unmatched, matched or newly generated matched samples.
The authors welcome further research collaborations in using the data or the accompanying research instruments.
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Residues of organochlorine pesticides in fruits, vegetables and tubers from Nigerian markets
No full textAssessment of Industrial Pollution Load in Lagos, Nigeria by Industrial Pollution Projection System (IPPS) versus Effluent Analysis
No full textNon
Assessment of atmospheric profile of some heavy metals in barks of Parkia biglobosa (African locust bean) trees
No full textNatural resource exploitation involving the mining of iron-ore from earth's deposits result in the release of aerodynamic size particulate
metals, dusts and other atmospheric pollutants. The atmospherics baseline levels some iron-ore associated heavy metals were assessed
around Itakpe iron-ore deposit, North Central Nigeria, using tree barks of African locust bean (Parkiabiglobosa) as indicator. Tree barks
of P. biglobosa were randomly scaled off dried and digested using standard procedures. The digests were quantified for Cd, Mn, Cr, Ni,
Cu, Zn and Pb in flame of Unicam 969 atomic absorption spectrophotomer. The concentration of Zn, 20.387-52.07 mg/kg was the highest in respect of other metals determined, followed by Mn, 8.74-24.18 mg/kg and then Pb, 2.95-8.66 mg/kg. Cu levels ranged 0.68-3.14 mg/kg, Ni, 0.34-3.12 mg/kg and Cr, 0.34-0.91 mg/kg. Cd concentration was the least; 0.16-0.48 mg/kg in barks of P. biglobosa trees. The overall mean concentrations (mg/kg) were: Zn, 34.21 ± 4.09; Mn, 13.59 ± 2.04; Pb, 25 ± 0.75; Cu, 1.34 ± 0.34; Ni, 1.18 ± 1.05; Cr, 0.55 ± 0.09; and Cd, 0.33 ± 0.06, with availability sequence is in the order Zn > Mn > Pb > Cu > Ni > Cr > Cd. The detected heavy metals levels in the barks of P. biglobosa trees were variable, and may be a function of vegetation proximity/orientation to source points, plant distribution/population density, level of exposure and atmospheric stability, which is dependent on prevailing climatic factors. The evaluated P. biglobosa barks did not contain the heavy metals at concentrations capable of impacting negatively on the plant. Thus, the tree barks concentration of the evaluated metals were within natural concentration levels, and are therefore regarded as not polluted. This implies that atmospheric levels of the aerodynamic particulates heavy metals were low and not hazardous. The detected levels could serve as
baseline concentration for monitoring against potential atmospheric deposit build up of heavy metals when mining becomes fully operationa
Water quality issues in developing countries – A case study of Ibadan Metropolis, Nigeria
No full textWater quality issues in developing countries – A case study of Ibadan Metropolis, Nigeria
Voudouris K & Voutsa D (eds): Water Quality Monitoring and Assessment
Rijeka, Croatia: InTech Online Publishers, 2012, pp 541-560, ISBN 978-953-51-0486-5To describe water as the engine of life will not constitute an overstatement. This is because
water in its various forms, accounts for more than 70 per cent of the entire earth surface and all life forms regardless of their habitat depend on this abundant resource for their continuous existence. However, as huge as this vital resource is, only small percentage of its natural form could be readily used for drinking and sanitation purposes by man. These are normally stored up in repositories and embankments such as the aquifers, lakes, rivers and other surface freshwater bodies. Due to the increasing influence of natural ev
ents and anthropogenic activities on these natural water sources, the pristine characteristics exhibited by these water sources often fade out with time. Today, the understanding of
water quality has become conceptualized because of the numerous uses to which different types of water could be subjected to. More so, due to the complexity of several factors determining water quality and the countless choice of variables used to provide quantitative
evaluation of this term, it is difficult to adopt a single definition of water quality (Chapman,1996). In a simple term, however, water quality refers to the composition of any
water body as affected by nature and human cultural activities, expressed in terms of both measurable quantities and narrative statements (Novotny, 2003). Depending on the area of application, the criteria for establishing water quality requirements differ in many aspects. Hence, water which is suitable for a particular purpose, for instance, agricultural irrigation
might not be useful for other purposes due to differences in water quality requirements.
The causative factors responsible for the deteriorating water quality in most developing
countries are quite similar. For instance, the city of Ibadan which is the largest indigenous
city in Africa has several inter-related factors which directly or indirectly impact the quality
of water bodies within the city. These are largely due to improper waste disposal, poor physical planning and increasing population pressures on the dilapidated infrastructures
within the city. Omoleke (2004) also identified the culture of the indigenous people living in
the core of the city as a vital factor contributing to these menace.Traditionally, the city been a commercial centre for local marketers of maize, yam and other food stuffs where heaps of refuse are generated on a daily basis. Due to the clustered distribution of old houses within the interior of the city, the mechanised collection of these refuse becomes virtually impossible. Hence, people resort to dumping their solid wastes into drains and stream channels which often results into clogging and flooding. More so, most of the houses around these areas do not have toilet facilities, as such people defecate indiscriminately on undeveloped plots of land or along the streams and rivers within the city. These uncivilized behaviours have continued to aggravate many dimensions of water pollution problems within the city
Eco-partitioning and indices of heavey metal accumulation in sediment and Tilapia zillii fish in water catchment of River Niger at Ajaokuta, North Central Nigeria
No full textIn this study the distribution and accumulation indices of some heavy metals in sediments and Tilapia zillii fish in freshwater catchment of River Niger by Ajaokuta Steel Company (ASC), North Central Nigeria were investigated. Water, bottom sediments and Tilapia zilliifish samples were collected upstream and downstream of the drainage column by ASC, Ajaokuta. The sample were digested according to standard methods and analysed for Cd, Mn, Cr, Ni, Cu, Zn and Pb using flame atomic absorption spectrometer. Accumulation indices or factor (AI or AF) of the investigated heavy metals were defined using the ratio of mean concentration Co in component/organism and that in the surrounding water Cw at steady state (AI/AF = Co/Cw). Sediment accumulation indices (AI) of the metals were: Cd, 5.4; Mn, 3.4; Cr, 1.6; Ni, 12.5; Cu, 1.6; Zn, 25.9 and Pb, 411.6, while the AI of the metals in fillets of T. zillii were Cd, 3.0; Mn, 2.1; Cr, 1.6; Ni, 5.1; Cu, 4.6; Zn, 3.2 and Pb, 14.0. Seasonal climate changes induces little marginal or no changes in the AIs of the metals except for Pb (841.5, 411.6) and Cd (11.6, 5.4) in sediment, and Pb (32, 14) and Cd (5.3, 3.0) (p<0.05) in fish fillets. Thus significant changes in metal AIs may be the consequence of their concentration levels in the aquatic ecosystem. Therefore, accumulation indices or factors may be an estimate of ecosystem status, and may be a useful tool for monitoring and predictive risk assessment (MPRA) purposes
Comparative assessment of some heavy metals in some inland fresh water fish species from River Niger and River Osara in North Central Nigeria
No full textThe concentration levels of Cadmium(Cd), Manganese(Mn), Chromium(Cr), Nickel(Ni),
Copper(Cu), Zinc(Zn) and Lead(Pb) were determined in fish fillets of some inland fresh
water fish harvested from River Niger at Ajaokuta and River Osara at Itakpe North Central
Nigeria. Eighty samples each of Tilapia zillii, Oreochromis niloticus, Sarotherodon galileaus
and Clarias anguillaris were collected from both rivers and digested using standard methods.
The metals were determined using Unicam 969 Flame Atomic Absorption Spectrophotometer
fitted with deuterium lamp. The levels of heavy metals detected in the fish fillets of the
different species varies with mean concentrations (mg/kg) in the range: Mn, 3.14±1.12-
5.77±0.95 in Sarotherodon galileaus-5.30±1.48-10.48±2.57 in Tilapia zillii; Zn, 1.06±0.84-
5.67±1.42 in Oreochromis niloticus-2.08±1.13-4.21±1.80 in Clarias anguillaris; Cu,
1.54±0.65-3.30±0.79 in Tilapia zillii-3.00±1.07-6.23±1.79 in Sarotherodon galileaus; Cr,
1.49±0.71-3.16±0.65 in Tilapia zillii-2.44±0.61-4.60±2.24 in Clarias anguillaris; Ni,
0.76±0.13-1.56±0.52 in Tilapia zillii-1.74±0.95-3.25±1.19 in Clarias anguillaris; Pb,
0.02±0.03-0.02±0.01 in Tilapia zillii-0.51±0.09-0.83±0.09 in Oreochromis niloticus, and Cd,
0.02±0.01-0.04±0.01 in Tilapia zillii-0.14±0.04-0.18±0.04 in Oreochromis niloticus. The
differences in heavy metal levels in the different fish species examined were not significant
(p>0.05), except for Mn in Tilapia zillii which was significantly higher (p<0.05) than in other
species. This is probably because each fish species concentrated the heavy metals differently.
Clarias anguillaris fillets appeared to hold the metals more except for Zn, followed by
Oreochromis niloticus, Sarotherodon galileaus, and Tilapia zillii in that order. The detected
levels were however below the WHO/FAO guideline limit in food substances, fish and
fishery products. The study showed that there were differences in concentrations of Cd, Mn,
Cr, Ni, Cu, Zn and Pb in fillets of Tilapia zillii, Oreochromis niloticus, Sarotherodon
galilaeus and Clarias anguillaris, implying that the fishes concentrated the heavy metals
differently. The levels of heavy metals detected in all the fish species were within the natural
background levels
Baseline studies of some heavy metals in top soils around the Iron - ore Mining Field Itakpe North Central Nigeria
No full textThe baseline concentration levels of cadmium(Cd), manganese(Mn), chromium(Cr), nickel(Ni), copper(Cu) zinc(Zn) and lead(Pb) were determined in the top soil around the iron ore deposit at Itakpe North Central Nigeria in order to define benchmark concentrations as a basis for future environmental monitoring and pollution control for sustainable environmental protection. One hundred and sixty soil samples were randomly collected over an area of 5x5km2 between December 2003 and November 2005. The soil samples were subjected to standard methods and analysed using Unicam 969 flame atomic absorption spectrophotometer. The pH and organic carbon concentration of the soil ranged 4.28-7.46 (6.56±0.70) and 2.60-5.60% (2.85±1.00%) respectively. The mean concentration levels of heavy metals ranged: Zn, 43.89±9.06-75.29±15.74 mg/kg; Cu, 33.48±7.44-51.50±7.35 mg/kg; Pb, 18.73±2.87-33.31±4.31 mg/kg; Mn,
6.39±1.07-20.31±3.42 mg/ kg; Cr, 8.18–14.89 mg/ kg; Ni, 11.99±2.71-20.84±2.09 mg/kg; and Cd, 0.10±0.05-0.21±0.07
mg/kg. The soil metals concentration sequence was Zn > Mn > Pb > Ni > Cu > Cr > Cd, with Zn having the highest relative abundance in topsoil in respect to the measured metals while Cd had the least. There was decreasing gradient in the heavy metals concentrations from top soil (0–15cm) to depth 110cm. Zinc concentration level decreased by 23.92% from 67.65 mg/kg top soil to 13.06 mg/ kg at 100–110 cm; Mn, 21.5% from 20.30-4.30 mg/kg; Cr, 14.09% from 14.89-1.84 mg/kg; Ni, 16.65% from 16.88-2.41 mg/ kg; and Cu, 19.54% from 45.99-7.52 mg/ kg, from top soils to depth of 100–110 cm respectively. Cadmiumand lead were found below the instruments detection limit (i.e. < 0.002, Cd and < 0.05, Pb) at depth 50–110 cm and 100-110 cm respectively. Apparently, the soil environments are yet to be impacted negatively by heavy metals because heavy metal levels around Itakpe iron ore deposit and beneficiation plant were within natural concentration levels, and are therefore regarded as not polluted
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