Worldwide Hospitality and Tourism ThemesEmerald Article: e-Learning as a tool to improve quality and productivityin hotelsManuela SarmentoArticle information:To cite this document: Manuela Sarmento, (2010),"e-Learning as a tool to improve quality and productivity in hotels", WorldwideHospitality and Tourism Themes, Vol. 2 Iss: 4 pp. 398 - 409Permanent link to this document:http://dx.doi.org/10.1108/17554211011074056Downloaded on: 31-03-2012References: This document contains references to 14 other documentsTo copy this document: firstname.lastname@example.orgThis document has been downloaded 595 times.Access to this document was granted through an Emerald subscription provided by UNIVERSITI TEKNOLOGI MARAFor Authors:If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service.Information about how to choose which publication to write for and submission guidelines are available for all. Additional helpfor authors is available for Emerald subscribers. Please visit www.emeraldinsight.com/authors for more information.About Emerald www.emeraldinsight.comWith over forty years experience, Emerald Group Publishing is a leading independent publisher of global research with impact inbusiness, society, public policy and education. In total, Emerald publishes over 275 journals and more than 130 book series, aswell as an extensive range of online products and services. Emerald is both COUNTER 3 and TRANSFER compliant. The organization isa partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archivepreservation. *Related content and download information correct at time of download.
The current issue and full text archive of this journal is available at www.emeraldinsight.com/1755-4217.htmWHATT2,4 e-Learning as a tool to improve quality and productivity in hotels Manuela Sarmento398 Research Centre on Tourism, Innovation and Service, ´ University Lusıada, Lisbon, Portugal Abstract Purpose – The purpose of this paper is to analyze the contribution of e-learning in the improvement of quality and productivity in hotels. Design/methodology/approach – The methodology is based on an inquiry answered by 34 hotels that are using e-learning. For this purpose, a survey on ﬁve, four and three star hotels, located throughout Portugal, was conducted between January and March 2009. Findings – The research reveals that hotels consider that e-learning increases productivity and production volume. On the other hand, e-learning contributes signiﬁcantly to employees’ motivation. The paper also concludes that managers’ opinions about e-learning strategies are dependent on the hotel category and head-ofﬁce nationality. Originality/value – e-Learning is based on information and communication technology and supports the educational process. Owing to the important results achieved, e-learning is continuously gaining relevance in hotels, and in educational institutions. As such, analysing the contribution of e-learning for quality improvement in hotels brings originality to the research whilst adding value to the body of knowledge in the industry. Keywords E-learning, Hotel and catering industry, Portugal, Quality Paper type Research paper Introduction In a knowledge society, people must be able to update their knowledge in order to cope with the rate of change. e-Learning is a powerful tool that can help to facilitate the objectives of training and education (Abbey, 2000; Hartley, 2001). It is an application of computer science based on information technology and the internet that allows the individual to control aspects of the content, the learning process, and the application of learning (Lee et al., 2000; Machado, 2000). These factors in conjunction with the relatively low delivery costs can help to optimize investment in training. The objectives of e-learning are in essence to achieve: . productivity enhancement; . quality improvement; and . cost reduction (Horton, 2000; Rosenberg, 2000). The scope of this research paper is to analyse the contribution of e-learning to the improvement of quality and productivity in hotels.Worldwide Hospitality and TourismThemes e-Learning conceptVol. 2 No. 4, 2010pp. 398-409 The idea of using computers as a learning tool is not new, and e-learning is one ofq Emerald Group Publishing Limited several concepts (others include: ﬂexible learning, distance learning, telelearning and1755-4217DOI 10.1108/17554211011074056 computer supported learning) that link similar learning methodologies (Conole, 2004).
As an established and widely adopted approach to distributed learning, the wider e-Learningsocio-cultural factors are still being explored (Martin and Webb, 2001). to improve There are numerous deﬁnitions for e-learning: Falch (2004) suggests that e-learningrepresents “the use of new multimedia technologies and the internet to improve the quality qualityof learning by facilitating access to resources and services as well as remote exchangesand collaboration”. At its simplest level, e-learning is little more than the use of electronictools and technologies to assist us in our teaching and learning. The term has evolved in 399recent years, along with e-commerce and e-business, linked to the extremely rapid growthand uptake of internet useage. The creation of virtual communities may in time replace orprovide alternatives to the traditional bricks-and-mortar classroom (Martin and Webb,2001). The wider concept of e-learning also includes innovation elements in relation toother kind of technologies used in education, and it presents a value added contribution tolearning. (Nagi, 2006).The analytical dimensions of e-learningAdvances in information technology and new developments in methodologies provideopportunities to create e-learning environments that are: . well designed; . learner centered; . interactive; . affordable; . efﬁcient; and . accessible.On the other hand, an e-learning project requires the participation of a multidisciplinaryteam, due to his multiple dimensions. But what are the analytical dimensions of thisphenomenon? The answers are not always easy to identify, due to the relative immaturityof e-learning. Khan (2001) suggests that there are eight dimensions to an e-learning framework: (1) institutional; (2) pedagogical; (3) technological; (4) interface design; (5) evaluation; (6) management; (7) resource support; and (8) ethical.In Khan’s e-learning framework, each one of the eight dimensions has a special role anddepends on the others. The ﬁnal result is the addition of these eight dimension. Zualkernan (2006) offers a constructivist view of e-learning, based on a frameworkthat has ﬁve dimensions and each dimension have two variables. The ﬁnal result is theaddition of these ﬁve dimensions:
WHATT (1) Learner characteristics. Cognitive and constraints learning styles plus goals and2,4 motivations. (2) Physical environment. Available information plus successful action. (3) Structural characteristics. Available information plus cognitive and constraints learning styles.400 (4) Semantic characteristics. Successful action plus goals and motivation. (5) Task environment. Adaptation between physical environment and learner. The research The research presented in this paper sought to analyse and evaluate the relationship between e-learning versus quality and productivity in hotels. The methodology was based on an inquiry with responses from 34 hotels that were using e-learning. For this purpose, we surveyed hotels with ﬁve, four and three stars, located throughout Portugal, between January and March 2009 (Tourism of Portugal, 2008). The following sections outline the data analysis methods, the survey implementation, the sample characterization, and the cause-effect relationship between the ten strategic factors and the hotel categories. The research is also intended to identify groups of hotels that are sharing comparable strategies for e-learning, quality management and productivity. Methodology and analysis The project was based on a survey with 40 questions. We used the Likert scale with ﬁve levels, 1 ¼ nothing, 2 ¼ little, 3 ¼ moderate, 4 ¼ much and 5 ¼ strong, in order to measure the strategies pursued by hotels, concerning e-learning. The market research commences with survey validation done by a panel with ten hotel managers. To analyze the survey, we built the database and we used the statistical software package SPSS 16.0. The statistical methods applied were as follows: . Descriptive analysis: to gauge the frequency and percentage of the hotels characterization, as well as the mean value, standard deviation, maximum and minimum values of the ten strategic factors under investigation. . Bivariate analysis, namely the x 2-test: to evaluate whether the survey responses given by hotel managers about the ten strategic factors are dependent or independent of hotel category, location and head-ofﬁce nationality. . Cluster analysis: to determine homogenous groups, whereby each element of a group is more similar to the other elements of this group than to the elements of any other group. . One-way analysis of variance: to check whether there are signiﬁcant differences within the groups identiﬁed via cluster analysis and to characterise each group. Survey implementation and identiﬁcation of the sample A total of 250 survey questionnaires were sent by post to hotels that were using e-learning in Portugal. We received 41 survey replies, but only 34 were valid, since seven were rejected due to several missing values. The hotel’s characterization – category, location in Portugal and head-ofﬁce nationality – is shown in Figures 1-3.
Hotel category e-Learning Five stars, eight; 24% to improve Three stars, 14; quality 41% 401 Figure 1. Four stars, 12; Hotel category 35% Hotel location Madeira, seven; Azores, 0; 0% 21% North, five; 15% Centre, four; 12% Algarve, eight; Lisbon and 23% Figure 2. Alentejo, two; Tagus Valley, Hotel location six% eight; 23% Head office nationality Other, 15; 44% Figure 3. Portuguese, Hotel head- 19; 56% ofﬁce nationalityThe sample has 41 per cent of three star hotels and the minimum percentage is 24 per centof ﬁve star hotels. The main regions that answered the survey were Algarve and the Lisbon regionwith 23 per cent of the total answers, representing 46 per cent of the sample andMadeira Islands represents 21 per cent. Head-ofﬁce nationality is mainly Portuguese (56 per cent). Other nationalitiesrepresent 44 per cent of the sample. The mean value, standard deviation, maximumand minimum of the ten strategic factors under investigation are presented in Table I.These factors were obtained through the application of principal components analysis.
WHATT The highest mean value (xm) was obtained in Factor 10 “e-learning decreases training2,4 costs” (xm ¼ 4.29) and the lowest mean value in Factor 9 “e-learning decreases the absenteeism” (xm ¼ 2.53). The answer to the Factor 1 “e-learning increases productivity” is the most consensual (s ¼ 0.52) and to the Factor 8 “e-learning decreases employees turnover” is less consensual (s ¼ 1.11). Figure 4 shows the mean values of the factors in decreasing order.402 The global mean value for the ten factors is xm ¼ 3.59, and there are six factors, which have mean values superior to it. However, if we consider the scale mean value, there are seven factors, which mean values are above 3. Thus, the importance of e-learning in hotels is indubitable. The percentage for each scale level and per strategic factor is shown in Table II. The highest percentage value was 47.1 per cent obtained in level 4 of Factor 3 “E-learning increases the performance quality level”. The lowest percentage of 0 per cent occurred in Factor 4 “e-learning increases the performance quality level” in level 1. Relationship between hotels identiﬁcation and survey responses To determine whether a company strategy is dependent or independent of the identiﬁcation variables (category, location and head-ofﬁce nationality), the x 2-test was used. Factors Mean value SD Minimum Maximum 1 e-Learning increases productivity 4.15 0.52 1 5 2 e-Learning increases production volume 4.09 0.72 1 5 3 e-Learning increases the performance quality level 4.06 0.72 2 5 4 e-Learning increases the employees motivation 3.71 0.86 1 5 5 e-Learning increases the employees satisfaction 3.15 0.86 1 5Table I. 6 e-Learning increases the employees salaries 2.85 0.86 1 5Mean, standard 7 e-Learning decreases the time for the task execution 4.15 0.85 1 5deviation, minimum 8 e-Learning decreases employees turnover 2.94 1.11 1 5and maximum values 9 e-Learning decreases the absenteeism 2.53 0.91 1 5of the factors 10 e-Learning decreases training costs 4.29 0.86 1 5 Mean values of e-learning factors 10 e-learning decreases training costs 4.29 7 e-learning decreases the time for the task execution 4.15 1 e-learning increases productivity 4.15 2 e-learning increases production volume 4.09 3 e-learning increases the performance quality level 4.06 4 e-learning increases the employees’ motivation 3.71 MV Mean value 3.59 5 e-learning increases the employees’ satisfaction 3.15 8 E-learning decreases employees’ turnover 2.94Figure 4. 6 e-learning increases the employees’ salaries 2.85Mean values of 9 e-learning decreases the absenteeism 2.53e-learning factors 1 2 3 4 5
e-Learning Nothing 1 Little 2 Moderate 3 Much 4 Strong 5Factors (%) (%) (%) (%) (%) to improve 1 e-Learning increases productivity 0.0 5.9 17.6 32.4 44.1 quality 2 e-Learning increases production volume 0.0 2.9 23.5 35.3 38.2 3 e-Learning increases the performance 403 quality level 2.9 5.9 11.8 41.2 38.2 4 e-Learning increases the employees motivation 0.0 14.7 20.6 44.1 20.6 5 e-Learning increases the employees satisfaction 8.8 17.6 35.3 26.5 11.8 6 e-Learning increases the employees salaries 14.7 20.6 38.2 17.6 8.8 7 e-Learning decreases the time for the task execution 0.0 5.9 14.7 38.2 41.2 8 e-Learning decreases employees turnover 14.7 26.5 26.5 14.7 17.6 Table II. 9 e-Learning decreases the absenteeism 14.7 38.2 32.4 8.8 5.9 Frequency percentage10 e-Learning decreases training costs 0.0 5.9 14.7 23.5 55.9 per strategic factorThe x 2-test compares the observed and expected frequencies of two variablesof the sample. The H0 checks whether it is possible to accept the hypothesis ofindependence between these variables within the population. The H0 is tested againstthe alternative Ha. To test the independence of variables, the T statistic equation (1)is used: X ðFoi 2 Fei Þ2 n T¼ ð1Þ i¼1 FeiWhere Fei the expected frequency is veriﬁed for category (1) of each variable; Foi is theobserved frequency for category (1) of each variable; (Foi 2 Fei) is the differencebetween the observed and the expected frequency for the crosstab (1). The comparison between Pearson and a signiﬁcances, allows accepting or rejectingthe null hypothesis. If Pearson signiﬁcance is less than 5 per cent there are no reasonsto accept the H0. Table III shows the results and conclusions of the x 2-test applied to the factorsand hotels category, location and head-ofﬁce nationality. Managers’ opinions are independent from the hotel category, location and head-ofﬁcenationality in four factors, namely: in Factor 4 “e-learning increases the employeesmotivation”, in Factor 7 “e-learning decreases the time for the task execution”, in Factor 9“e-learning decreases the absenteeism“ and in Factor 10 “e-learning decreasestraining costs“. However, the opinion given to Factor 8 “e-learning decreases employees turnover”is dependent on hotel category, location and head-ofﬁce nationality. Table IV reveals that the answers to questions are independent on hotels category(60 per cent), location (90 per cent) and head-ofﬁce nationality (50 per cent).
2,4 404 Table III. identiﬁcation WHATT factors and hotels Relationship between Category Location Head ofﬁce Pearson Pearson PearsonFactors signiﬁcance Conclusion signiﬁcance Conclusion signiﬁcance Conclusion 1 e-Learning increases productivity 0.145 Independent 0.245 Independent 0.001 Dependent 2 e-Learning increases production volume 0.221 Independent 0.362 Independent 0.000 Dependent 3 e-Learning increases the performance quality level 0.000 Dependent 0.131 Independent 0.000 Dependent 4 e-Learning increases the employees’ motivation 0.088 Independent 0.301 Independent 0.099 Independent 5 e-Learning increases the employees’ satisfaction 0.002 Dependent 0.143 Independent 0.602 Independent 6 e-Learning increases the employees’ salaries 0.000 Dependent 0.721 Independent 0.000 Dependent 7 e-Learning decreases the time for the task execution 0.074 Independent 0.123 Independent 0.084 Independent 8 e-Learning decreases employees’ turnover 0.000 Dependent 0.274 Dependent 0.327 Dependent 9 e-Learning decreases the absenteeism 0.287 Independent 0.089 Independent 0.431 Independent10 e-Learning decreases training costs 0.274 Independent 0.384 Independent 0.211 Independent
Determination of groups e-LearningCluster analysis was used in order to identify groups of hotels sharing the same to improveopinions about e-learning. On this basis, hotels within any one group are implementingsimilar strategies, distinct from those used by hotels belonging to other groups. quality The cluster analysis used, attempts to identify groups of hotels based on tenstrategic factors, using a speciﬁc algorithm. The division into four groups is theappropriate solution, using the Ward method and squared Euclidean distance. This 405solution can be validated using one-way analysis of variance and conﬁrmed throughthe discriminant analysis. This analysis demonstrates that 100 per cent of the assembled hotels are correctlyclassiﬁed in the four groups. Each strategic group is denominated according to therelevant strategic factor and has the following number of hotels: . Group 1: “e-Learning increases the employees’ motivation” – seven hotels. . Group 2: “e-Learning decreases the time for the task execution” – 15 hotels. . Group 3: “e-Learning increases productivity” – eight hotels. . Group 4: “e-Learning decreases training costs” – four hotels.The one-way analysis of variance tests the hypothesis of equal means amongst thegroups. If the mean values of the groups are equal, then the groups are not different inrespect to the ten strategic factors. All the preconditions required and steps concerningthis analysis, including the Levene and F-test were accomplished, whereby we canconclude that there are four different groups. The mean values of the factors for eachgroup are displayed in Table V: . Factors 1: “e-learning increases productivity” and 2 “e-learning increases production volume” have the maximum mean value at group 3 and the minimum at group 1. . Factors 3: “e-learning increases the performance quality level” and 4 “e-learning increases the employees motivation” have the maximum mean value at group 1 and the minimum at group 2. . Factors 5: “e-learning increases the employees’ satisfaction” and 6 “e-learning increases the employees salaries” have the maximum mean value at group 4 and the minimum at groups 2 and 1, respectively. . Factor 7: “e-learning decreases the time for the task execution“ has the maximum mean value at group 2 and the minimum at group 4. . Factor 8: “e-learning decreases employees turnover” has the maximum mean value at group 1 and the minimum at group 3. . Factor 9: “e-learning decreases the absenteeism” has the maximum mean value at group 2 and the minimum at group 4.Hotels identiﬁcation Dependent factor (%) Independent factor (%) Table IV.Category 40 60 PercentageLocation 10 90 of dependent/Head-ofﬁce nationality 50 50 independent responses
WHATT Group 1 Group 2 Group 3 Group 4 Total2,4 seven 15 eight four 34 hotels hotels hotels hotels hotels Factors 20% 44% 24% 12% 100% 1 e-Learning increases productivity 3.30 4.40 4.80 4.10 4.15 2 e-Learning increases production volume 3.50 3.60 4.74 4.50 4.09406 3 e-Learning increases the performance quality level 4.22 3.84 4.18 4.00 4.06 4 e-Learning increases the employees’ motivation 4.34 3.00 3.70 3.80 3.71 5 e-Learning increases the employees’ satisfaction 2.50 2.20 3.40 4.50 3.15 6 e-Learning increases the employees’ salaries 1.96 3.63 1.60 4.22 2.85 7 e-Learning decreases the time for the task execution 4.14 4.50 4.20 3.74 4.15 8 e-Learning decreases employees’ turnover 3.33 3.10 2.16 3.16 2.94Table V. 9 e-Learning decreases the absenteeism 2.60 2.95 2.46 2.12 2.53Mean values of factors 10 e-Learning decreases training costs 4.47 3.70 3.99 5.00 4.29for each group Mean value 3.44 3.49 3.52 3.91 3.59 . Factor 10: “e-learning decreases training costs” has the maximum mean value at group 4 and the minimum at group 2. The maximum mean value of all groups is presented by group 5 (xm ¼ 5.00) and the minimum by group 2 (xm ¼ 3.70). Table VI shows how each group is compound in percentage as far as the hotel category, location and head-ofﬁce nationality are concerned. Characterization of the strategic groups As shown in the previous section, the hotels in the sample can be aggregated into four strategic groups. Each group has distinct approach in relation to e-learning versus ´ quality and productivity. The groups’ characterization was based on Scheffe test, F-test and mean values of the ten factors. Group 1: “e-learning increases the employees’ motivation” This group of hotels represents 20 per cent of the sample. It includes hotels pertaining to three and four stars, whereby 29 per cent of the hotels are located in the centre of Portugal and in Algarve. About 71 per cent of the hotels are Portuguese. e-Learning conclusions. This group has a mean value of xm ¼ 3.44, denoting that hotels moderately consider that e-learning is a critical factor for the increasing of productivity regarding the ten strategic factors. The hotels pertaining to this group consider that e-learning strongly decreases training costs (xm ¼ 4.47), increases very much the employees motivation (xm ¼ 4.34) and also increases the performance quality level (xm ¼ 4.22). These hotels assume that e-learning increases the employees salaries in a low level (xm ¼ 1.96).
Group 1 Group 2 Group 3 Group 4 Total 34 e-Learning seven hotels 15 hotels eight hotels four hotels hotels to improve 20% 44% 24% 12% 100% qualityHotels characteristics xm ¼ 3.44 xm ¼ 3.49 xm ¼ 3.52 xm ¼ 3.91 xm ¼ 3.59CategoryFive stars (%) 7 38 100 24Four stars (%) 14 40 63 35 407Three stars (%) 86 53 41LocationNorth of Portugal (%) 14 13 25 15Centre of Portugal (%) 29 13 12Lisbon and Tagus Valley (%) 14 20 25 50 23Alentejo (%) 13 6Algarve (%) 29 20 25 25 23Madeira Islands (%) 14 20 25 25 21Azores Islands (%)Head ofﬁcePortuguese (%) 71 47 63 50 54 Table VI.Nationality CharacteristicsOther country (%) 29 53 38 50 46 of hotels per groupGroup 2: “e-learning decreases the time for the task execution”This group of hotels is the largest of the sample representing 44 per cent. Among thefour groups, this has the highest percentage of three star hotels 53 per cent, which arelocated all over the country, being 53 per cent foreign hotels. e-Learning conclusions. This group has a mean value of xm ¼ 3.49, expressing amoderate concern about the ten strategic factors. The hotels belonging to this groupstrongly consider that e-learning decreases the time for the task execution (xm ¼ 4.50)and increases productivity (xm ¼ 4.40). However, e-learning increases the employeessatisfaction in a low level (xm ¼ 2.20).Group 3: “e-learning increases productivity”This group of hotels represents 24 per cent of the total sample. Of all groups, this has thehighest percentage of four star hotels 63 per cent, located in north of Portugal (25 per cent),Lisbon (25 per cent), Algarve (25 per cent) and Madeira (25 per cent).The hotels are mainlyPortuguese 63 per cent. e-Learning conclusions. Group 3 has a mean value of xm ¼ 3.52 which meansthat hotels demonstrate a moderate opinion about the ten factors under investigation.The hotels pertaining to this group highly consider that e-learning increases productivity(xm ¼ 4.80) and production volume (xm ¼ 4.74). However, these hotels hardly believe thate-learning increases the employees salaries (xm ¼ 1.60).Group 4: “e-learning decreases training costs”This group of hotels is the smallest representing 12 per cent of the sample. About 100 percent are ﬁve star hotels, mainly located in Lisbon region. The hotels are half Portugueseand half foreign. e-Learning conclusions. This group has the highest overall mean value of xm ¼ 3.91expressing a proﬁle with a profound interest in the ten strategic factors. They strongly
WHATT think that e-learning decreases training costs (xm ¼ 5.0), and increases employees2,4 satisfaction (xm ¼ 4.50). The minimum mean value (xm ¼ 2.12), is expressed in e-learning decreases the absenteeism. In conclusion, the data analysis reveals that most hotels consider that investing in e-learning training, will increase productivity and performance quality levels. In general, terms, hoteliers belief that if they can implement e-learning effectively, it will improve408 quality and productivity levels and consequently enhance proﬁtability and customer satisfaction (employees and clients). Summary and conclusions The main purpose of the research presented in this paper was to analyse the relationship between e-learning, quality and productivity. The hotels selected for the sample were those who used e-learning as a method of education and training for their employees. Strategic proﬁles of three, four and ﬁve star hotels were studied on the basis of ten strategic factors and by considering their location and head-ofﬁce nationality. This research was based on a survey carried out between January and March 2009. In 250 surveys sent directly to the general managers, 34 valid answers were received and afterwards processed using the statistical software package SPSS 16.0. The research reveals that hotels consider e-learning to be a key determinant in the effort to improve productivity and quality, since the mean values of the factors “e-learning increases productivity” and “e-learning increases production volume” are xm ¼ 4.15 and 4.09, respectively. e-Learning accounts for a signiﬁcant increase in the production volume of the hotels in the survey (73.5 per cent), the productivity level (76.5 per cent) and the performance quality level (79.4 per cent) of the hotels. Additionally e-learning greatly decreases the task execution time in 79.4 per cent of the hotels. e-Learning also contributes to motivation levels (xm ¼ 3.71). The inﬂuence of e-learning is less evident in terms of reducing absenteeism (xm ¼ 2.53) and turnover (xm ¼ 2.94). Overall, the hotels in the sample consider that e-learning greatly enhances the competitiveness regarding the ten strategic factors (xm ¼ 3.59). Further, the research reveals four organised groups which have independent strategic proﬁles and behaviour in terms of their approaches to evaluating the impact of e-learning on quality and productivity. Their mean values are superior to moderate: group 1 xm ¼ 3.44, group 2 xm ¼ 3.49, group 3 xm ¼ 3.52, and group 4 xm ¼ 3.91. The managers’ e-learning strategies are dependent on the hotels’ category in 40 per cent and on head-ofﬁce nationality in 50 per cent. In synthesis, the competitiveness of the hotels is related to its intellectual capital. e-Learning consolidates and transforms knowledge into competitive advantage, especially in terms of increasing productivity and performance levels. It is clear that e-learning participants who are better informed and attempting to stay in touch with change are key to driving sustainable development in ever evolving markets. References Abbey, B. (2000), Instructional and Cognitive Impacts of Web-based Education, Idea Group Publishing, Hershey. Conole, G. (2004), “e-Learning: the hype and the reality”, Journal of Interactive Media in Education, Vol. 12, available at: www-jime.open.ac.uk/2004/12
Falch, M. (2004), “A study on practical experiences with using e-learning methodologies and e-Learning cooperative transnational development methodology”, CTI Working Paper No. 97, Center for Tele-Information, Lyngby. to improveHartley, D.E. (2001), On-demand Learning: Training in the New Millennium, HRD Press, Amherst. qualityHorton, W.K. (2000), Designing Web-based Training: How to Teach Anyone Anything Anywhere Anytime, Wiley Computer, New York, NY, available at: www.elearning06.com/eLAP2006/ Proceedings/p7.1-6-ﬁn-51-keynote-Kuldeep%20Nagi.pdf 409Lee, W., Diana, L. and Bass, J. (2000), Multimedia-based Instructional Design: Computer-based Training, Web-based Training, and Distance Learning, Jossey Bass/ Pfeiffer, San Francisco, CA.Machado, J. (2000), e-Learning em Portugal, Editora, Lisboa.Martin, E. and Webb, D. (2001), “Is e-learning good learning?”, e-Learning, Ethics and Equity Conference, Equity and Social Justice, Victoria University, Melbourne, pp. 49-60.Nagi, K. (2006), “Solving Ethical Issues in e-Learning”, paper presented at Third International Conference on e-Learning for Knowledge-Based Society.Rosenberg, M.J. (2000), e-Learning: Strategies for Delivering Knowledge in the Digital Age, McGraw-Hill, New York, NY.Zualkernan, I.A. (2006), “A framework and a methodology for developing authentic constructivist e-learning environments”, Educational Technology & Society, Vol. 9, pp. 198-212.Further readingNewbold, P. (1995), Statistics for Business and Economics, 4th ed., Prentice-Hall, Englewood Cliffs, NJ. ´Sarmento, M. (1997), “Behavior of quality groups facing key variables”, Tecnica, Vol. 2, pp. 17-27.Sarmento, M. (1999), On the Impact of World Expositions: The Case of Lisbon Expo’98, BIE, Paris.Corresponding authorManuela Sarmento can be contacted at: email@example.comTo purchase reprints of this article please e-mail: firstname.lastname@example.orgOr visit our web site for further details: www.emeraldinsight.com/reprints