Long-term organic matter effect and the response to compressive stress

Density and permeability of a loess soil:Long-term organic matter effect and the response to compressive stress

E.Arthur a ,?,P.Schj?nning a ,P.Moldrup b ,M.Tuller c ,L.W.de Jonge a

a Department of Agroecology,Faculty of Science and Technology,Aarhus University,Blichers Allé20,P.O.Box 50,DK-8830Tjele,Denmark

b Department of Biotechnology,Chemistry and Environmental Engineering,Aalborg University,Sohngaardsholmsvej 57,DK-9000Aalborg,Denmark c

Department of Soil,Water and Environmental Science,University of Arizona,Tucson,AZ 85721,USA

a b s t r a c t

a r t i c l e i n f o Article history:

Received 7May 2012

Received in revised form 30August 2012Accepted 3September 2012

Available online 18November 2012Keywords:Resistance Resilience Void ratio Compaction

Pore organisation Initial water content

Long-term ?eld trials provide an ideal means to assess effects of cultivation practises (e.g.,fertilisation,tillage,crop rotation etc.)on soil physical properties and soil fertility.To build upon the knowledge of the role of organic carbon (OC)and other soil properties on soil response to compressive stress,undisturbed soil cores were collected from a long-term fertilisation experiment in Bad Lauchst?dt in Germany,including combinations of animal manure and mineral fertilisers.The cores were drained to ?100hPa matric potential and exposed to uniaxial con ?ned compression (200kPa).Investigated indicators for compression response included compression index,precompression stress,and resistance and resilience indices based on measured soil physical properties (air permeability,and void ratio).Soil resilience was assessed following exposure of compacted cores to freeze –thaw (FT)and wet –dry (WD)cycles.The OC content increased with increased fertilisation and resulted in decreased initial bulk density,higher air-?lled and total porosities,and increased organisation of the pore space.Soil resistance decreased with increasing OC content but the correlation was not signi ?cant.However,initial bulk density (ρbi )and initial gravimetric water content (w i )were signi ?cant-ly positively correlated to the indices of soil compression resistance,with the effect of ρbi being signi ?cantly stronger.Signi ?cant recovery of air-?lled void ratio and air permeability was observed following exposure to FT and WD cycles,with the latter cycle showing higher recovery levels.The OC and ρbi signi ?cantly in ?uenced the magnitude of recovery following FT cycles,with ρbi showing contrasting trends on void ratio after both WD and FT cycles.It was concluded that the main drivers in ?uencing soil response to com-pressive stress are ρbi and w i .No direct in ?uence of OC was observed,rather the indirect effect of OC was seen through lower ρbi and greater w i associated with higher OC levels.Further studies are required to differ-entiate the relative effects of OC,ρbi and w i for variably-textured soils.

?2012Elsevier B.V.All rights reserved.

1.Introduction

Physical properties of soils only slowly change in response to cul-tivation practices like crop rotation and fertilisation;therefore long-term ?eld experiments are essential for assessment of the impact of agricultural management.For example,fertilisation studies conducted over a period of 100years in Askov in Denmark show a 23%increase in soil organic carbon (OC)relative to unfertilised condi-tions,a decrease in top-soil bulk density,and an increase in soil strength following amendment with animal manure (AM)or mineral

NPK fertilisers (Schj?nning et al.,1994).Investigating samples from the same site,Munkholm et al.(2002)revealed that aggregates from AM amended plots were more stable when wet and less stable when dry relative to aggregates from plots with no AM amendments,which showed higher stability under dry conditions.They attributed this to the differences in dispersible clay content.Additionally,Watts and Dexter (1997)found that increased OC,arising from 47years of different crop rotation practices,decreased the rate at which clay dispersibility increased with water content.They also showed that while aggregate stability decreased with declining OC,aggregate tensile strength was comparatively insensitive to changes in OC.For the more than 100years old Broadbalk wheat experiment at Rothamsted in the UK,Blair et al.(2006a)showed a signi ?cant impact of AM and mineral N fertilisation on soil aggregation and unsaturated hydraulic conductivity of a silt loam soil.For the 105years long ‘static fertilisation ’experiment in Bad Lauchst?dt (BL)in Germany,which involved application of different rates of sole AM and AM in combination with mineral NPK fertiliser,Koppen and Eich (1991)and Blair et al.(2006b)reported increasing soil OC

Geoderma 193–194(2013)236–245

Abbreviations:AM,animal manure;OC,organic carbon;k a ,soil air permeability;ε,air-?lled porosity;e T ,total void ratio;e a ,air-?lled void ratio;e w ,water-?lled void ratio;Ф,soil total porosity;ρbi ,initial dry bulk density;w i ,initial gravimetric soil water content;σ,applied stress;C c ,compression index;σpc ,precompression stress;PO,pore organisation index;RS,compression resistance index;RL,compression resilience index.

?Corresponding author.Tel.:+4587154756.

E-mail address:emmanuel.arthur@agrsci.dk (E.

Arthur).0016-7061/$–see front matter ?2012Elsevier B.V.All rights reserved.

https://www.wendangku.net/doc/f48506372.html,/10.1016/j.geoderma.2012.09.001

Contents lists available at SciVerse ScienceDirect

Geoderma

j ou r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /g e o d e r m a

and mean weight diameter of aggregates with increasing application rates of AM.For the BL experiment,Eden et al.(2012)also found an increase in air-?lled pore space with increasing OC content for a matric suction range of?100to?1000hPa,which they associated to differences in fertilisation.This gave rise to higher gas diffusivities for soils with high-organic carbon content.

Other long-term studies at various locations show similar results. For example,Rasool et al.(2008)reported an increase in total soil porosity and aggregation due to32years of fertilisation on a sandy loam in India.Yang et al.(2011)showed an increase in water retention in fertilised plots compared to control plots after19years in dry land areas of the Chinese Loess Plateau.A recent study has emphasised the importance of such long-term studies in improving our understanding of mechanisms and processes in soils(Petersen et al.,2012).To further increase our understanding of long-term effects on the physical state of a particular soil,evaluation and analysis of the resistance of developed physical properties to compaction stress and their recovery rate over time is of essence.Soil compaction resulting from agricultural opera-tions(tillage,fertiliser applications and harvesting with heavy machin-ery)leads to undesirable changes in soil physical properties with signi?cant agronomic consequences(Soane and van Ouwerkerk,1994).

In-depth knowledge about the effects of long-term fertilisation and associated increases in OC on the compressive behaviour of soils is crucial for prediction of the changes that might occur when soils are subjected to stresses imposed by agricultural machinery (McBride,1989).Besides potential resistance to externally imposed stress it is essential to also quantify the recovery(resilience)follow-ing stress cessation.Knowledge gained from studying OC effects on soil resistance and resilience will serve as a basis for development of indices for soil vulnerability.For example,soils with low compres-sion resistance may be endured if the resilience—ability to recover—is high,while low resistance in combination with a low resilience is problematic(Gregory et al.,2007).The major soil properties identi-?ed as affecting compaction resistance and/or resilience are texture (Horn,1988;McBride,1989),organic matter content(O'Sullivan, 1992;Soane,1990;Zhang et al.,1997),moisture content(Larson et al.,1980;McBride,1989),and bulk density(Keller et al.,2011;Paz and Guérif,2000).Soil properties especially sensitive to compaction are air permeability,gas diffusivity,and hydraulic conductivity (Arthur et al.,2012a;Berisso et al.,2012;Viklander,1998).

The objective of our study was to reveal long-term fertilisation effects on pore characteristics of a loess soil and to identify the main driver(s)controlling resistance and resilience of various soil physical properties(bulk density,air-?lled porosity,air permeability and com-ponents of the void ratio)to compaction stress based on samples col-lected from the Bad Lauchst?dt site in Germany.

2.Materials and methods

2.1.Experimental site

The Bad Lauchst?dt static fertilisation experiment is located in Saxony-Anhalt,Germany(51°24′N,11°53′E).The mean annual temperature and precipitation for the years1963–2008were9.7°C and585mm,respectively.The soil is a silt loam with26%clay (b2μm),65%silt(2–50μm),and9%sand(50–2000μm)on average. This long-term experiment on a Haplic Chernozem(Altermann et al., 2005)was established in1902and modi?ed in1978.A detailed description of all applied treatments is provided in K?rschens and Pfefferkorn(1998).

Sampling took place in spring2008in a?eld(strip3)with a 4-year crop rotation(winter wheat[Triticum aestivum],sugar beet [Beta vulgaris],spring barley[Hordeum vulgare],and potato[Solanum tuberosum])during the winter wheat season.Tillage operations included an offset disc plough(30-cm depth)followed by harrowing prior to sowing of the winter wheat.The main?eld is divided into three blocks differing in AM management(0,20,and30t ha?1per 2years).Each block has six sub-treatments with different mineral fertilisation strategies,which gives a total of18treatments.The experiment has no true replicates.The present study addressed six treat-ments:the3rates of AM,and with or without NPK mineral fertiliser. Note that,Mx denotes the amount of manure added and±indicates if NPK was added or not.For example,M2+means20t ha?1of AM in combination with NPK and M3?indicates30t ha?1of AM with no NPK.Further details and a schematic of the sampling areas used for this study are given in Eden et al.(2012)and Vendelboe et al.(2012).

2.2.Sampling and measurements

2.2.1.Soil properties before compression

For each plot,12undisturbed100cm3soil cores(height3.5cm; diameter6.1cm)were taken next to each other from two sampling locations(six from each location)about7m apart at a depth of6to 9.5cm.Soil water retention(using tension tables),and air permeabil-ity(k a)(using the steady state method of Iversen et al.(2001))were measured for all core samples at matric potential of?100hPa.Bulk soil sampled adjacent to cores sampling locations was analysed for soil texture,particle density,and soil OC content(Eden et al.,2012).

The air?lled porosity(ε)of each core was calculated from a com-bination of volumetric soil water content and total porosity(Φ) which in turn was derived from soil bulk density(ρb)and particle density.The soil pore organization index(PO)was calculated as k a/εat?100hPa.

https://www.wendangku.net/doc/f48506372.html,pression test

For the soil resistance and resilience to compression,the following properties were used as functional indicators:k a,total void ratio(e T), air-?lled void ratio(e a)and water-?lled void ratio(e w).After equili-bration of the soil cores at?100hPa,their weight and height(H) (using a specially constructed caliper with6replicate measurements) were determined to enable the calculation of e T,e a,and e w using Eqs.(1)to(3).

e T?

ρs H?d

ρb H

?1e1Te a?e T?ε100=Φ

eTe2T

e w?e T?e ae3T

where d is the displacement of the soil in cm after compression.For ini-tial e T,d=0.Theε100is the air-?lled porosity at?100hPa.The com-pression test involved subjecting soil cores at?100hPa to uniaxial con?ned compression to a maximum load of200kPa at a constant rate of2mm min?1(Koolen,1974)followed by unloading at the same rate.The data acquisition was equidistant on a time scale,with a constant strain of0.03mm s?1,giving about1300data points for constructing the stress–strain curve.This compression stress simulates that imparted by agricultural machinery(e.g.Gregory et al.,2007; Lamandéand Schj?nning,2008).The weight,d and ka of the soil cores were measured immediately(b2min)after compression and unloading.Thereafter,six of the12cores for each plot were subjected to two wet–dry(WD)cycles,comprising?5hPa in a sand tension table for24h,and drying at40°C for another24h followed by satura-tion(via capillary rise for24h)and re-equilibration at?100hPa.The remaining six cores were subjected to two freeze–thaw(FT)cycles comprising freezing at?10°C for24h and saturation/re-equilibrating at?100hPa in a sand tension table.The FT and WD cycles were repeat-ed once(total of two cycles)because the d,e T and ka of the soil did not differ signi?cantly(p>0.05by Student's t test)between the two cycles. After completion of the cycles,all soil cores were oven-dried at105°C for24h.

237

E.Arthur et al./Geoderma193–194(2013)236–245

To estimate the general resistance to compression,the compression index (C c )was used.To obtain C c ,we modelled the soil compression data (applied stress,σ,and e T )using the Gompertz (1825)model (Eq.(4))as suggested by Gregory et al.(2006)by non-linear regression analysis.

e T ?a tc exp ?exp b log 10σ?m eTeT?

e4T

where a ,b ,c and m are the free model parameters.Because of the low stress applied (200kPa)in the study,m was constrained at m ≤log 10200kPa=2.305during model ?tting to avoid obtaining erroneous values of C c when the in ?ection point falls outside the range of the measured data (Keller et al.,2011).The value of a approximately corresponds to the lower (?nal e T )asymptote,while a +c is the upper (initial e T )asymptote (Gregory et al.,2006).The C c was estimated using Eq.(5)as suggested by Gregory et al.(2006).C c ?

bc exp 1eT

e5T

Additionally,the pre-compression stress (σpc )was estimated as the stress at maximum curvature of the compression curve (Gregory et al.,2006;Keller et al.,2011).

When considering the speci ?c soil properties (k a ,e T ,e a ,e w ),the resistance (RS)and resilience (RL)of the measured variables for the different treatments were estimated using Eqs.(6)and (7)as pro-posed by Arthur et al.(2012b).RS ?100?C 0?D c j j

C 0 ?100

e6T

RL ?

D x ?D c j j

D c

?100e7T

where C 0is the original (no load)value,D c is the value immediately after compression and D x is the value following WD or FT cycles.For a given variable,the RS index is bound by 0(no resistance)and 100(full resistance);the RL index is bound by 0(no resilience)and an inde ?nite upper limit (interpretable as a percentage of the stressed state).We used Eq.(7)as an estimate of RL because for soils with dif-ferent initial functions/properties,we believe it better re ?ects how the function/property in question has improved as compared to the stressed situation.Other studies have used resilience indices taking into account the pre-stressed soil property (e.g.Arthur et al.,2012a;Grif ?ths et al.,2000).The RS and RL of various soil properties were then related to soil organic carbon,initial bulk density,and gravimet-ric water content to establish the dominant driver (s).2.3.Statistical analyses

For comparison of the soil properties before compaction,the Kruskal –Wallis non-parametric test in SPSS 19(SPPS Inc.,Chicago,USA)was used to test for signi ?cant differences (p b 0.05)between the means of all variables for the different experimental plots.This test was used because it does not assume normality in the data and is much less sensitive to outliers.When signi ?cant differences occurred among the experimental plots,the Mann –Whitney U test was used to differentiate between the means.The Gompertz model was parameterised using the non-linear regression analysis (solver)feature in Microsoft Excel.Linear and non-linear regression model tests were conducted with SPSS 19.The experimental design of the ?eld trial with no true replicates prevents a real test of the effects of fertilisation strategy on the soil parameters studied.Hence,we will discuss our results primarily in relation to OC and the associated soil bulk density,which displayed a true gradient mirroring the

long-term fertiliser application rates.The intra-plot variation between individual soil cores was used as residual error in the above-mentioned tests of differences between experimental plots.3.Results and discussion

https://www.wendangku.net/doc/f48506372.html,anic carbon,bulk density and soil pore characteristics at ?eld capacity

Application of organic and mineral fertiliser for more than a centu-ry resulted in a gradient in soil organic carbon (OC)from 1.5%to 2.4%with increasing rates of fertiliser application (Table 1;Eden et al.,2012)which is in close agreement with previous measurements (Blair et al.,2006a;Koppen and Eich,1991;K?rschens,2006).There was a signi ?cant negative correlation between OC and initial soil bulk density (ρbi ),with a corresponding increase in Φwith increasing OC (Fig.1)(Arvidsson,1998;Ekwue,1990;Soane,1990).This was expected due to the dilution effect caused by mixing of the added organic material with the denser mineral fraction of the soil (Bronick and Lal,2005;Courtney and Mullen,2008)and —more importantly —the OC-facilitated aggregation of organo-mineral com-plexes in higher OC soils (Tisdall and Oades,1982).However,as reported earlier (Eden et al.,2012),the M3+plot showed a higher ρbi than expected from the general trend with OC,similar to the M2?plot.This is due to the location of that plot within the larger ?eld.The M3+was the outermost plot and was located close to a farm road.Hence,the speed and perhaps depth of tillage operations for this plot most probably were different from the other plots.In addition,the speci ?c sampling location was likely affected by traf ?c to and from the experimental ?eld.Because of this,the exceptionally high ρbi of M3+was considered an outlier and not used in subse-quent regression tests where ρbi was expected to play a prominent role.To put the ρbi of the present study in context,we compared the ρbi with what was expected given the texture and OC content.Heinonen (1960),based on analysis of 111soils from Southern Fin-land,proposed a pedotransfer function for estimating the ρbi of ?elds which have naturally settled for 2–4years after the last tillage opera-tion (Eq.(8)).

ρbi ?1:40?0:072OC ?0:0013Clay t0:0014Sand

e8T

where OC,clay and sand contents are all in g per 100g of soil.One would normally expect that the ρbi values measured for the Bad Lauchst?dt soils will at least be equal to or lower than the predictions from Eq.(8)because they were tilled (ploughed)just 6months prior to sampling.However,the ρbi values of all the plots were much higher than expected (Fig.1),suggesting that we are dealing with a special soil with respect to natural density and structure.This is largely due to the high silt content which gives the soil a massive structure with a relatively low degree of aggregation (considering the clay content).This makes the intact soils similar to sieved-repacked samples as also observed by Eden et al.(2012)when they measured gas diffusivity for the same soils.

Table 1

Soil texture,organic carbon contents,and bulk densities of investigated soils (Eden et al.,2012).Treatment

Clay (b 2μm)Silt

(2–50μm)

Sand

(50–2000μm)

Organic carbon

Particle density %by weight

Mg m ?3M0?26.465.87.8 1.53 2.66M0+26.566.37.2 1.82 2.65M2?26.664.98.5 2.01 2.65M2+26.665.38.1 2.18 2.64M3?25.765.09.3 2.22 2.65M3+

25.6

61.9

12.5

2.37

2.63

238 E.Arthur et al./Geoderma 193–194(2013)236–245

At ?eld capacity (?100hPa),volumetric soil water content,θ,increased signi ?cantly with increasing AM application rates.Further,ε,e T ,and k a increased signi ?cantly when the fertilisation rate was above 20t ha ?1of AM in combination with NPK (Table 2).The k a was especial-ly low for the M3+plot (signi ?cantly lower than M0+),re ?ecting the speci ?c conditions for this plot.The k a ,and pore organisation,PO (k a /ε)are important indices for characterising soil pore geometry and hence soil structure (Blackwell et al.,1990;Groenevelt et al.,1984;Moldrup et al.,2001),with highly structured soils usually having greater k a and PO values.The PO for the different plots as a function of εis shown in Fig.2a,with isolines of k a (3,6and 9μm 2)added for comparison.The two plots with OC>2.1%showed signi ?cantly higher PO when com-pared to the rest with bulk densities above 1.55Mg m ?3(Fig.2a;Table 2).This means that the two high-OC plots not affected by traf ?c (M2+and M3?)have higher conductance of soil air per unit volume of ε.

To identify the main driver behind the improved PO for the soils,OC and ρbi were tested as predictors of PO by means of linear regres-sion modelling (excluding M3+).The ρbi was a stronger predictor of PO (Fig.2b;r 2=0.89;p=0.017)than OC (r 2=0.70,p=0.078).The M3+,with traf ?c-induced high ρbi had the lowest PO,and was close to the other two high density plots,despite the higher OC;indi-cating a different soil structure compared to the other plots (Fig.2b).Thus,although the trend in ρbi resulted from the OC gradient (Fig.1),it was the ρbi ,rather than OC which showed a clear relationship with pore connectivity and arrangement.This negative relationship between ρbi and pore connectivity was also observed by D?rner et al.(2010)for an Ultisol for four different matric potentials.

3.2.Resistance to compaction

Analysis of the resistance to compaction was conducted in two ways.First,the parameters (C c and σpc )obtained from the Gompertz model (Eqs.(4)and (5))were used as general indicators for the soil's compaction resistance.Second,the resistance of speci ?c soil proper-ties (k a e T ,e a ,e w )to compaction was assessed using Eq.(6).After-wards,three soil properties (OC,ρbi ,and initial water content,w i ),expected to have an in ?uence on compaction resistance,were evalu-ated using correlation and multiple regression analyses.The results are presented in Table 3,Figs.3,4and Table 4.

Considering the parameters of the Gompertz model,a small C c value indicates that a particular soil is more resistant to compression and vice versa,while a small σpc value re ?ects a low resistance.The C c index is normally interpreted as the strength of the ‘virgin ’part of the soil structure when exposed to compressive stresses higher than pre-viously experienced (https://www.wendangku.net/doc/f48506372.html,rson et al.,1980).The σpc index,in turn,is regarded an estimate of this pre-compression threshold (Lebert and Horn,1991).The Gompertz equation is commonly used to identify the σpc and C c for soils at much higher stresses (up to 800kPa in Keller et al.,2011)than applied here.Strictly speaking,it is possible that stopping the load at 200kPa may not provide standard ‘geotechni-cal ’estimates of both parameters.However,since model ?ts for all soil cores were good (mean r 2=0.99;root mean squared error=0.0014),the estimates given are accurate for comparison purposes.

The C c values ranged from 0.018to 0.177with a mean of 0.05(Fig.3a).These values are on the low end when compared to previous studies (Arthur et al.,2012a;Keller et al.,2011),implying a general higher resistance of this soil to compression.The σpc ranged from 24to 94kPa,with an average of 60kPa for all soils (Fig.3b).There was no signi ?cant difference in σpc among the experimental plots (except the M3-).Generally,pressures exerted on the topsoil by tyres on agri-cultural machinery range from 70to 375kPa with even higher stress for some high-pressure tyres (Schj?nning et al.,2012;Soane,1986).Thus,the σpc values obtained in this study can be considered as low,but they are in agreement with other studies on recently tilled arable land (Horn,2004;Krümmelbein et al.,2010).Also,since sampling was done 6months after ploughing and the sites used for sampling had not been wheeled,we do not interpret the σpc as classical estimates of pre-compression by mechanical loads (which identi ?es the highest load the soil has been subjected to previously)but rather a re ?ection of the strength of the “collection ”of aggregates in the middle of the pro-cess of “age hardening ”.“Age hardening ”in soils occurs due to two mechanisms:(i)formation of particle-particle bonds and (ii)reinforce-ment of the existing particle-particle bonds by cementation mecha-nisms (Dexter et al.,1988).Age-hardening increases compression resistance (Utomo and Dexter,1981)via increases in ρbi which subse-quently accounts for the differences observed in C c and σpc .

The k a ,with RS values ranging from 12to 40%,was most suscepti-ble to compression.The RS of the remaining properties were in the order e w >e T >e a .The RS values of the components of void ratio clear-ly showed that the decrease in e T was mainly due to decrease in e a ,rather than e w .The relatively low resistance of k a compared to e a and e T has also been shown earlier by Arthur et al.(2012b)where the range in RS ka was between 20and 40%for a copper contaminated ?eld.Although k a depends on e a (McCarthy and Brown,1992),the big difference in the RS values of k a and e a is because the remaining pore spaces are not interconnected and hence does not conduct air from and to the atmosphere.The seemingly higher RS of k a for the M3+plot is mainly because it already had very low k a at ?100hPa (Table 2)and the relative reduction was much lower compared to the other plots.

3.2.1.In ?uence of OC

Mean values were used for examining the in ?uence of OC on the compression resistance of the soils since only one OC

measurement

Fig.1.Relationship between initial bulk densities and soil organic carbon contents (regression excludes M3+).Different symbols represent the different plots.△M0?,▲M0+,□M2?,■M2+,○M3?,●M3+.Error bars denote standard error of the mean (SEM).Open diamonds denote predictions of natural bulk density from Heinonen (1960).

Table 2

Soil density,porosity,water content,and pore characteristics (at -100hPa matric potential)of experimental plots.Treatment

Initial bulk density Water content Air-?lled porosity

Total void ratio

Air permeability Mg m ?3

m 3m ?3μm 2M0? 1.64a 0.30b 0.076b 0.61d 2.59bc M0+ 1.61b 0.31b 0.079b 0.65c 3.54b M2? 1.56c 0.32a 0.087b 0.69b 4.24b M2+ 1.48d 0.32a 0.118a 0.79a 7.71a M3? 1.44e 0.32a 0.135a 0.85a 15.13a M3+

1.54c

0.33a

0.082b

0.71b

1.83c

Different letters indicate that means are signi ?cantly different (p b 0.05).

239

E.Arthur et al./Geoderma 193–194(2013)236–245

was conducted per experimental plot.Again,the M3+plot was excluded the analysis due to reasons discussed above.For the ?ve remaining plots,there was a positive correlation between OC and C c and σpc ,and negative correlations with all the other indicators of compression resistance,RS (Table 3).Besides σpc and RS ka ,all other indices had r values higher than 0.60,however,none of these correla-tions were signi ?cant.This indicates a trend of decreasing compres-sion resistance with increasing OC for all the indicators.Soane (1990)reviewed studies on the effect of the amount,composition and distribution of OC on soil compactibility and concluded that OC should in principle reduce soil susceptibility to compaction.Also,O'Sullivan (1992)applied static loads of 25–800kPa on soils (clay b 20%;OC 1.7–3.7%)from three tillage treatments and found a signi ?cant positive in ?uence of OC on compaction resistance.Howev-er,Smith et al.(1997),using soils with a wide range in clay and OC (clay 8-66%;OC,0.3-5.8%)showed that the effect of OC on compac-tion behaviour (using C c )of soils ceases to be signi ?cant beyond clay contents of 25%.Additionally,Zhang et al.(1997)and Arthur et al.(2012a)using soils with clay contents ranging from 4.5to 50%also found no signi ?cant effect of OC on soil compaction behaviour.The effect of OC on soil compressive resistance is likely to be con-founded by ρbi and w i as was also shown by Arthur et al.(2012a),where they used covariate analyses to determine the effect of OC while isolating the contribution of w i .The same could be done here to isolate the effect of both ρbi and w i ,but the absence of true repli-cates and the single measurements of OC per plot limits this option.An alternative is to examine the in ?uence of OC via the complexation

of clay based on the theory that 1g of OC is associated with 10g of clay (Dexter et al.,2008).The clay in excess of OC complexation is termed non-complexed clay (NCC).The NCC signi ?cantly affects soil properties such as aggregate strength and clay dispersibility (de Jonge et al.,2009;Schj?nning et al.,2012).The amount of NCC showed stronger negative correlations with C c and σpc ,and positive correlations with the RS indi-ces than OC.However,the correlations were still insigni ?cant (Table 3).A possible reason for the lack of a signi ?cant effect of OC (or NCC)on the measures of soil compression (especially C c )could be due to the high clay (>25%as noted by Smith et al.,1997)and high silt content of the soil.Smith et al.(1997)found highest C c values for ?ne-textured soils (clay+silt>50%)with OC as high as 4.23%and their reasoning was that the relatively high speci ?c surface area of these soils limits the ex-tent to which OC can interfere with the mineral particle interfaces to limit

compression.

Fig.2.(A)Soil pore organisation (PO =air permeability/air-?lled porosity)as a function of air ?lled porosity at ?100hPa.Air permeability (k a )isolines are shown.(B)Relationship between PO and initial bulk density (regression excludes M3+).Different symbols represent the different plots.△M0?,▲M0+,□M2?,■M2+,○M3?,●M3+.Error bars denote SEM.Different letters indicate that means are signi ?cantly different (p b 0.05).

Table 3

Correlation between soil organic carbon (OC),non-complexed clay (NCC),initial bulk density (ρbi ),and initial gravimetric water content (w i ),and the compression index (C c ),precompression stress (σpc )and indices of soil resistance (RS).Numbers in table are correlation coef ?cients (r ).Compression resistance OC a NCC ac ρbi

b w i

b C

c 0.78ns ?0.82ns ?0.88??0.66??σpc

0.65ns ?0.70ns

?0.45??0.36?RS air permeability ?0.37ns 0.39ns 0.34??0.31?RS total void ratio

?0.76ns 0.82ns 0.87???0.59??RS air-?lled void ratio ?0.73ns 0.77ns 0.78???0.58??RS water-?lled void ratio

?0.76ns

0.82ns

0.87???0.58??

Correlations exclude M3+;a averaged values used (n=5);b values from individual cores used (n=60);c calculated according to Dexter et al.(2008),please consult text;ns Correlation is not signi ?cant;**.Correlation is signi ?cant at the 0.01level;*.Correlation is signi ?cant at the 0.05

level.

Fig.3.(A)Compression index,C c ,and (B)precompression stress,σpc ,for experimental plots.Error bars denote SEM.Different letters indicate that means are signi ?cantly dif-ferent (p b 0.05).

240 E.Arthur et al./Geoderma 193–194(2013)236–245

3.2.2.In ?uence of initial bulk density and initial gravimetric water content

The assessment of the in ?uence of these two variables (ρbi and w i )was carried out in two steps.First,correlation analyses of the two var-iables with the Gompertz parameters and RS indicators were done separately using individual soil core data excluding the M3+plot (Table 3)in addition to linear regression analysis between average compression resistance and ρbi (Fig.4).Second,both ρbi and w i were used for multiple regression analyses as predictors of soil com-pression resistance (using all 72individual cores including M3+).3.2.2.1.Initial bulk density.There was a signi ?cant negative correlation between ρbi and the Gompertz model parameters (C c and σpc )and signi ?cant positive correlations with the RS indices (Table 3;Fig.4).The regression equations for the lines in Fig.4(excluding Fig.4a)showed that ρbi accounted for an average of 85%of the variation in the RS for various variables.The weaker relationship for RS ka is partly due to the dependence of k a on other properties of the existing pore space (pore con ?guration and connectivity).The decrease in RS eT with decreasing ρbi is primarily due to the decreasing RS e a arising from the loss in ε.Although RS e w showed a signi ?cant increase with ρbi ,the range was much smaller (94–98%).As shown above,increased ρbi is associated with increased compression resistance (regardless of which indicator is used).This trend is in agreement with several stud-ies (Imhoff et al.,2004;Keller et al.,2011;Saf ?h-Hdadi et al.,2009)where C c was used to assess compression resistance.Soils with higher

ρbi and lower εare less compressible than their less-dense counter-parts.This is because denser soils have more intricate particle arrangement,less pore space available for particle movement and higher friction forces between particles.Thus,soil deformation becomes more dif ?cult with increase in bulk density (Paz and Guérif,2000).The negative correlation between σpc and ρbi is in dis-agreement with previous studies (Arthur et al.,2012a;da Veiga et al.,2007;Imhoff et al.,2004),which reported the opposite trend.As stated elsewhere,we used σpc as an estimate of the strength of the aggregates that had undergone age-hardening during the six months following tillage.Low ρbi soils had higher OC content and this likely improved the aggregate strength,hence the higher σpc .Similar to this study,Krümmelbein et al.(2010)reported a negative correlation between σpc and ρbi and noted the strength of the structure of recent-ly tilled or re-levelled is largely de ?ned by inter-particle and inter-aggregates forces,rather than the ρbi .

3.2.2.2.Initial gravimetric water content.There was a signi ?cant posi-tive correlation between w i and both C c and σpc and negative correla-tions with the RS indices (Table 3).Higher water contents resulted in lower compression resistance.Existing literature is con ?icting on the effect of w i on compression resistance (using C c and σpc ).Several authors (Imhoff et al.,2004;Larson et al.,1980)have shown that C c is independent of w i across different soil textures.However,studies by Saf ?h-Hdadi et al.(2009)and Zhang et al.(1997)reveal a negative correlation between w i and C c ,especially for clayey soils.Moreover,Arthur et al.(2012a)reported higher C c ,values for higher water contents for three similarly textured soils.In contrast with the present study,sev-eral investigations have reported increased σpc with decrease in soil water content and/or matric water potential (e.g.Arvidsson and Keller,2004;Rücknagel et al.,2012;Saf ?h-Hdadi et al.,2009).The positive rela-tionship between σpc and w i is attributed to a decline in cohesive forces arising from an increase in w i .For this study,the very narrow range in w i (0.18–0.22kg kg ?1)makes it dif ?cult to examine in detail the effect of water content.We believe that in this case,the effect of w i re ?ects differ-ences in ρbi (as explained in the subsequent section).

3.2.2.3.Bulk density and water content.Since both ρbi and w i were sig-ni ?cantly correlated with C c ,σpc and the RS indices,they were used together in multiple regression as predictors of

compression

Fig.4.Relationship between initial bulk density and the resistance (RS)of air permeability (A),total void ratio (B),air-?lled void ratio (C),and water-?lled void ratio (D)after compaction.Regressions exclude M3+.Different symbols represent the different plots.△M0?,▲M0+,□M2?,■M2+,○M3?,●M3+.Error bars denote SEM.The r 2and p values given denote the signi ?cance of the regression model.

Table 4

Relationship between compression index (C c ),precompression stress (σpc ;kPa),and other indices of compression resistance (RS;%),and initial bulk density (ρbi ;Mg m ?3)and initial gravimetric water content (w i ;g g ?1).Regression equation

r 2Signi ?cance C c =1.06?0.51ρbi ?1.05w i

0.84?σpc =237.7?109.1ρbi ?40.1w i

0.28?RS ka =–283.7+122.8ρbi +553.1w i 0.15?RS eT =–118.5+98.3ρbi +274.7w i 0.86?RS ea =–254.3+154.9ρbi +411.7w i 0.64?RS ew =28.12+32.29ρbi +89.57w i

0.86

?

k a ,air permeability;e T ,total void ratio;ea ,air-?lled void ratio;ew ,water-?lled void ratio.?Regression model is signi ?cant (p b 0.05),but w i is not signi ?cant (w i added no further improvement over modelling with ρbi ).?Regression model (including both variables)is signi ?cant (p b 0.05).

241

E.Arthur et al./Geoderma 193–194(2013)236–245

resistance.It must be noted that although the two predictor variables (ρbi and w i)were signi?cantly correlated(r=-0.85),further analyses of multicollinearity showed that the impact of collinearity among the two variables was low enough(Variance In?ation Factor b4;analyses not shown)for both of them to be used in the model.The regression models for all indicators of compression resistance were signi?cant (Table4).The regression equations(Table4)imply that the higher theρbi and w i,the higher the soil resistance to compaction.However, we note that while the relationship betweenρbi and the indicators (C c,σpc,and RS indices)was identical to the correlations seen earlier (Table3),the effect of w i shows an apparent contradiction to that observed earlier in Table3.This could be due to either increased pore water pressure during the compression tests or net suppression effects ofρbi on the in?uence of w i.To clarify,since there was a strong negative correlation betweenρbi and w i,it indirectly in?uenced the relationship between the indicators and w i.For example,in Table3, there was a positive correlation between C c and w i,and a negative correlation between C c andρbi.However,after multiple regression analyses(Table4),there was a negative relationship between C c and w i implying that the simple correlation does not take into account the indirect effect of w i via theρbi.To con?rm this,a simple one-way analysis of covariance usingρbi as a covariate was done.A cor-relation of theρbi-adjusted C c values(evaluated atρbi=1.55Mg m?3) and w i revealed a signi?cant negative correlation(r=?0.82;p b0.05). Similar analyses for the RS indices and w i revealed the same trend with positive correlations(data not shown).

There are some factors which should be taken into account when considering these results.First,all soils used in this study had the same texture.Second,the effect of water content was only assessed at a pre-compression matric potential of?100hPa(resulting in a narrow range of w i).Third,the exceptionally highρbi in comparison with other soil densities,and?nally the low maximum pressure (200kPa)used for compression.These results are valid for similarly textured soils since the effect of soil texture cannot be ruled out.For example,similar covariate analyses ofρb-calibrated C c and w i for pre-viously published data(Schj?nning,1999)with a wide range of soil textures showed no effect of w i on soil compression.Also,in wetter or dryer conditions,the effect ofρbi on w i will be different because ρbi primarily affects the macropores and hence the water holding capacity for less negative matric potentials.A higher or lower matric potential other than used here could lead to different conclusions. Further,other compression studies have used higher maximum pres-sures(up to800kPa),and this could also have an effect on the anal-yses of the factors affecting compression resistance.

To summarise this section,we note that the in?uence of OC con-tent can generally be seen as indirect—affecting compaction resis-tance,mainly through its in?uence onρbi.For the present soil, increasingρbi and w i is associated with higher compression resistance of the‘virgin’soil structure,while the precompression threshold is only dependent onρbi.The suppression effect ofρbi on the effect of w i on resistance implies that simple correlation analysis between w i and compression resistance,while disregarding the effects of other signi?cant variables(ρbi and maybe OC)could lead to erroneous con-clusions.Nevertheless,due to previously mentioned reasons,a direct effect of OC cannot be excluded and we suggest further studies to dif-ferentiate between the relative effects of OC,ρbi and w i.

3.3.Resilience to compaction

The resilience of the soils was estimated following exposure of the samples to separate FT and WD cycles.This was done because in nat-ural environments these cycles are dominating mechanisms for soil structure recovery.For clari?cation of Eq.(7),a RL value of100 means that the value for the measured variable after recovery was twice the value(100%higher than)obtained immediately after com-pression.The imposition of the?rst FT and WD cycles showed considerable recovery for all variables for all experimental plots (Figs.5,6),while the second cycle did not show any signi?cant differ-ence in recovery state following the?rst cycle.The RL ka following WD cycles showed remarkable recovery(>100%)compared to the RL e a (~40%)and RL eT(~12%).Similarly,after FT cycles,the RL ka was much higher than the RL of the other variables.Aside the effect of the cycles on k a recovery,it is important to recognise that the mea-surement method used could pose a challenge in that k a is sensitive to closure of pores at the very edge(top and bottom)of the soil cores when being compacted and this may have contributed to the higher recovery when the pores“opened”during the cycles.The re-markable recovery observed after imposing these cycles has been shown in several studies,where improvements inε(Pillai and McGarry,1999;Pires et al.,2005),k a(Arthur et al.,2012a; Viklander,1998)and soil volume(Pires et al.,2005;Viklander, 1998)were observed.However,previous studies are not in agree-ment on the minimum number of WD cycles required before signi?-cant changes in soil structure are noticed.While Rajaram and Erbach (1999)and the present study suggest that one WD cycle is enough to signi?cantly change several soil properties,other studies have suggested that a minimum of three WD cycles(Pardini et al.,1996; Sarmah et al,1996)are required.This disagreement could be due to differences in methodology used for the wet-dry and freeze-thaw cy-cles(e.g.type,intensity and duration of the cycles),soil texture,ex-tent of structural damage as well as the mineralogy of the soils involved.The WD cycles facilitate recovery of soil structure through mechanisms that occur during the two processes(wetting and dry-ing).The saturation process used for wetting causes expansion of the electrical double layer,and increased contact between clay parti-cles and aggregates.Also,the capillary rise method used to saturate the soils can cause slaking of the soil aggregates leading to modi?ca-tions in structure(Pires et al.,2005).During drying,retraction of the particles leads to reorientation and differential settling of?ner parti-cles between coarser particles resulting in a change in pore structure and increased porosity as shown by the RL values(Shiel et al.,1988; Tessier et al.,1990).The mechanisms involved in the FT cycles are not as strong as the WD cycles as seen from the magnitude of recov-ery(Fig.6).When soils are subjected to FT cycles,pore water turns into ice,resulting in a9%volume change,and formation of ice lenses. These lenses causes fractures and cracks in the soil matrix and upon thawing the developed cracks do not fully close due to soil cohesion (Viklander,1998).Relocation of?ne particles out of large pores dur-ing thawing may also free blocked pores and cavities(Chamberlain and Gow,1979).These processes accounted for the increase in k a after FT cycles.

3.3.1.Drivers controlling resilience in relation to recovery condition

For examining drivers controlling resilience of the soil following com-paction,all6plots were considered,since the index used(Eq.(7))only considers the value immediately after compaction and after recovery—without taking into account the original value.Although the results indi-cate that the structure of the M3+soil is different from the other plots in aspects other than just theρbi(e.g.Figs.2b and4a),we regard theρbi as the main difference.The consideration of the compressed state rather than the initial condition in estimating RL evens out the effects of the highρbi of the M3+plot.The in?uence of OC orρbi on RL due to WD cycles was insigni?cant for all variables(Figs.5,6).There were no signif-icant correlations between OC and the RL of k a or any of the void ratio components(data not shown).Also,RL ka showed no correlation with OC orρbi.Regression analyses(both linear and non-linear)of the compo-nents of e andρbi showed interesting trends.While increasingρbi tended to increase RL e a following WD cycles,the reverse was the case for FT cycles.For RL ew and RL eT following WD cycles,the relationship withρbi was non-linear,decreasing to aρbi of about1.55g cm?3and increasing afterwards.On the other hand,for FT cycles,the same RL parameters increased withρbi to a similar value(1.55g cm?3)and decreased

242 E.Arthur et al./Geoderma193–194(2013)236–245

afterwards.This could indicate that the two cycles act in opposite direc-tions in relation to ρbi and soil resilience.In both cases,however the “threshold ”ρbi of 1.55g cm ?3seems to be the point where the effect on soil RL reverses.This “threshold ”ρbi also approximately relate to the two signi ?cantly different groups of PO (Fig.2).Detailed explanation of the mechanisms involved in these trends is constrained by the limited number of treatments (six)and the non-signi ?cance of the regressions.There is therefore the need for further investigations into this using a combination of a wider range in texture,ρbi ,w i ,and OC to ensure more concrete conclusions.

4.Summary and conclusions

This study examined the dominant drivers affecting the resistance (using measured soil properties and modelling of compression data)and resilience of a loess soil to compressive stress using samples obtained from a 105-year long fertilisation experiment.Long-term fertilisation with organic and mineral fertilisers applied at different rates resulted in a gradient of organic carbon content which was re ?ected in decreased bulk density,greater air-?lled porosity and increased pore connectivity.The dominant drivers in ?uencing the

soil's

Fig.5.Effect of initial bulk density on the resilience (RL)of air permeability (A),total void ratio (B),air-?lled void ratio (C)and water ?lled void ratio (D)after wet –dry cycles.Different symbols represent the different plots.△M0-,▲M0+,□M2?,■M2+,○M3?,●M3+.Error bars denote SEM.The r 2and p values given denote the signi ?cance of the

regression.

Fig.6.Effect of initial bulk density on the resilience (RL)of air permeability (A),total void ratio (B),air-?lled void ratio (C)and water ?lled void ratio (D)after freeze –thaw cycles.Different symbols represent the different plots.△M0?,▲M0+,□M2?,■M2+,○M3?,●M3+.Error bars denote SEM.The r 2and p values given denote the signi ?cance of the regression.

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E.Arthur et al./Geoderma 193–194(2013)236–245

resistance to compaction were initial bulk density and gravimetric moisture content,with increasing compression resistance observed for soils with higher bulk densities and higher water contents.Climatic conditions(freeze–thaw and wet–dry cycles)signi?cantly facilitated recovery of soil properties following compaction.Additionally,the effect of initial bulk density on recovery of components of void ratio (total,air-?lled and water-?lled void ratio)was contrasting for the two cycle types.The effect of OC was minimal for both resistance and resilience to compaction.This suggests that although OC is important in its effect on soil bulk density,it had no signi?cant direct effect on the resistance and resilience to compaction.However,it is important to note that factors such pre-compression water content,texture as well as magnitude of the stress may be central in de?ning the role of OC and bulk density on soil response to compressive stress.Further studies are therefore required to clearly differentiate these relative roles.

Acknowledgements

The authors thank Ines Merbach from the Department of Communi-ty Ecology,Helmholtz Centre for Environmental Research(UFZ)for pro-viding access to sampling sites at the Static Fertilisation Experiment in Bad Lauchst?dt.The study was?nanced by the Danish Research Council for Technology and Production Sciences under the auspice of the Soil Infrastructure,Interfaces,and Translocation Processes in Inner Space (Soil-it-is)project.The assistance of Bodil B.Christensen and Fatemeh Razzaghi with laboratory work and compression data modelling is gratefully acknowledged.We also acknowledge the constructive sug-gestions and comments of two anonymous reviewers.

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2017山香教育理论基础整理笔记(教育学、心理学、教育心理学)

第一章教育与教育学 1、《学记》——“教也者，长善而救其失者也” 2、战国时荀子——“以善人者谓之教” 3、许慎在《说文解字》中认为“教，上所施，下所效也。”“育，养子使作善也。” 4、最早将“教育”一词连用的则是战国时期的孟子：“得天下英才而教育之，三乐也。” 5、分析教育哲学的代表人物谢弗勒在《教育的语言》中把教育定义区分为三种： 规定性定义：作者自己认为的定义，即不管他人使用的“教育”的定义是什么，我认为“教育”就是这个意思。运用规定性定义虽然有一定的自由度，但是，要求作业在后面的论述和讨论中，前后一贯地遵守自己的规定。 描述性定义：回答“教育实际上是什么”的定义。尽量不夹杂自己的主观看法，适当地对术语或者使用该术语的方法进行界定。 纲领性定义：回答“教育应该是什么”的定义。即通过明确或隐含的方式告诉人们教育应该是什么或者教育应该怎么样。 6、教育是一种活动。“教育”是以一种“事”的状态存在，而不是以一种“物”的状态出现。因而。我们就把“活动”作为界定教育的起点。 7、教育活动是人类社会独有的活动。 8、“生物起源论”代表人物： 利托尔诺在《各人种的教育演变》中指出教育是超出人类社会以外的，在动物界中就存在的。 沛西·能在《教育原理》中也认为教育是一个生物学过程，扎根于本能的不可避免的行为。 9、“终身教育”概念的提出，指明人在生理成熟后仍继续接受教育。 10、社会性是人的教育活动与动物所谓“教育”活动的本质区别。 11、教育的本质：教育活动是培养人的社会实践活动。 12、教育是人类通过有意识地影响人的身心发展从而影响自身发展的社会实践活动。 13、学校教育是一种专门的培养人的社会实践活动。 14、学校教育自出现以来就一直处于教育活动的核心。 15、学校教育是由专业人员承担的，在专门机构——学校中进行的目的明确、组织严密、系统完善、计划性强的以影响学生身心发展为直接目标的社会实践活动。 16、学校教育的特征：①可控性②专门性③稳定性 17、教育概念的扩展——大教育观的形成 18、1965年，法国教育家保罗·朗格朗在《终身教育引论》中指出，教科文组织应赞同“终身教育”的原则。 19、1972年，埃德加·富尔在《学会生存》中对“终身教育”加以确定，并提出未来社会是“学习化社会”。 20、“终身教育”概念以“生活、终身、教育”三个基本术语为基础。 从时间上看，终身教育要求保证每个人“从摇篮到坟墓”的一生连续性的教育过程； 从空间上看，终身教育要求利用学校、家庭、社会机构等一切可用于教育和学习的场所； 从方式上看，终身教育要求灵活运用集体教育、个别教育、面授或远距离教育； 从教育性质上看，终身教育即要求有正规的教育与训练，也要求有非正规的学习和提高，既要求人人当先生，也要求人人当学生。 21、教育的形态，是指教育的存在特征或组织形式。 22、在教育发展史上，教育的形态经历了从非形式化到形式化，再到制度化教育的演变。

教育学教育心理学理论及代表人物

教育学有关理论、代表人物 1、神话起源说—— 2、生物起源说——利托尔诺（法国） 3、心理起源说——孟禄（美国） 4、劳动起源说——马克思（前苏联） 5、中国史上第一部教育文献——《学记》——乐正克 6、西方较早讨论教育问题的着作——《论演说家的培养》（《雄辩术原理》）——昆体良（古罗马） 7、非制度化教育思潮——库姆斯、伊里奇 8、雄辩与问答法——苏格拉底（古希腊） 9、《理想国》——柏拉图（古希腊） 10、《政治学》——亚里士多德（古希腊） 11、教育学作为一门独立学科的萌芽——《大教学论》——夸美纽斯（捷克） 班级授课制，泛智教育。 12、首次提出把教育学作为一门独立的学科——培根（英国） 13、自然主义教育——《爱弥儿》——卢梭（法国） 14、教育学进入大学讲坛——康德（德国）、《林哈德与葛笃德》——裴斯泰洛齐（瑞士）

15、科学教育思潮的兴起，课程体系——《教育论》——斯宾塞（英国） 16、实验教育学——梅伊曼、拉伊（德国） 17、发展性教学理论——《教育与发展》——赞科夫（前苏联） 高难度进行教学的原则、高速度进行教学的原则、理论知识主导作用原则（重理性原则）、理解学习过程原则、对差等生要下功夫的原则 18、范例教学——瓦.根舍因（德国） 19、和谐教育思想——苏霍姆林斯基（前苏联） 20、《教育漫话》——洛克（英国） “白板说”、绅士教育、国民教育思想与民主教育思想。 22、规范教育学的建立——《普通教育学》——赫尔巴特（德国） 传统教育学代表、教师中心，教材中心，课堂中心、四段教学法、统觉观念。 23、实用主义教育学——《民本主义与教育》——杜威（美国） 现代教育学代表、教育即生长，教育即生活，教育即经验的改造或重组、在做中学、儿童中心主义。 24、第一部马克思主义的教育学着作——《教育学》——凯洛夫（前苏联） 25、我国第一部马克思主义的教育学着作——《新教育大纲》——杨贤江 26、设计教学法——克伯屈（美国）

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3中学教育心理学考试测试题第三章 学习的基本理论

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教育心理学主要理论知识

第一章做合格教师 第一部分主要理论知识 1．合格教师心理素质 教师心理素质是教师在专业发展过程中，在心理过程和个性心理特征两方面所表现出来的本质特征。 教师的心理素质包括如下方面，即教师的智力素质、教师的情感素质、教师意志素质、教师的教育教学素质、教师的人格素质、教师的信念。 2、教师的智力素质 教师的智力是从事教育工作应具备的基本心理素质，是教师从事教育教学工作的心理基础。教师的智力素质表现在以下方面： (1)敏锐的观察力(2)良好的记忆力(3)丰富的想象力⑷多方位的立体思维能力 ⑸注意分配的能力 3、教师的情感素质特点 教育过程是师生情感交流的过程，教育工作最大的特点就是以情感人。 (1)成熟而稳定的情感(2)爱的情感：对教育事业的热爱、对学生的热爱、对所教学科的热爱 4、教师的意志特点 (1)实现教育目的的自觉性(2)克服困难的坚韧性(3)选择教育决策的果断性(4)解决矛盾的沉着自制性 4．教师的教育能力素质 因材施教的教育能力、获取信息的能力、独创能力、教育科研能力、心理教育能力、教育机智 5．教师的教学素质：包括教师的知识结构与教学能力。 6．教师的知识结构 教师的知识水平是其从事教学工作的前提条件。根据有关专家的研究，教师的知识结构可由三方面组成，分别为本体性知识、实践性知识和条件性知识。 7．本体性知识。 教师职业的本体性知识是教师所具有的特定的学科知识，如语文知识、数学

知识等，也即人们所熟知的科目知识。 林崇德等人的研究表明，教师的本体性知识与学生成绩之间几乎不存在统计上的关系。 由于学科不同，本体性知识的具体内容是不同的。仅仅从一般意义上说，教师的本体性知识应包括四个方面：教师应对学科的基础知识有广泛而准确的理解，熟练掌握相关的技能、技巧；教师要基本了解与所教学科相关的知识点、相关性质以及逻辑关系；教师需要了解该学科的发展历史和趋势，对于社会、人类发展的价值以及在人类生活实践中的多种表现形态；教师需要掌握每一门学科所提供的独特的认识世界的视角、域界、层次及思维的工具与方法等。 8．实践性知识 教师的实践性知识是教师在开展有目的的教育教学活动过程中解决具体问题的知识，是教师教育教学经验的积累和提炼，它主要来源于课堂教育教学情景之中和课堂内外的师生互动行为，带有明显的情景性、个体性，体现出教师个人的教育智慧和教学风格。研究表明，教龄对教师的实践性知识存在着显著影响，教师的实践性知识水平随着教龄的增加而逐步上升。 9．条件性知识 教师的条件性知识是指教师所具有的教育学与心理学知识。条件性知识是：个教师成功教学的重要保障，而这种知识是目前广大的一般教师所普遍缺乏的。教师的条件性知识分为三个方面，即学生身心发展的知识、教与学的知识和学生成绩评价的知识。 正如杜威指出的那样，科学家的学科知识与教师的学科知识是不一样的，教师必须把学科知识“心理学化”，以便学生能理解。 10．教师的教学能力 教师的教学能力是教师从事教学活动，完成教学任务的能力，是教师专业能力的重要方面。 ⑴教学认知能力⑵教学设计的能力 ⑶教学操作能力：①表达能力②课堂组织管理能力③运用现代教育技术的能力