Abu-Al-Aish, A., & Love, S. (2013). Factors influencing students‘ acceptance of m- learning:  An investigation  in  higher  education. The  International  Review  of Research in Open and Distributed Learning, 14(5).

 

Al-Emran,  M.,  &  Salloum,  S.  A.  (2017).  Students'  Attitudes  Towards  the  Use  of Mobile Technologies in e-Evaluation. iJIM, 11(5), 195-202.

 

Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile   learning   in   higher   education. Computers   in   Human Behavior, 56, 93-102.

 

Alharbi, S., & Drew, S. (2014, August). Mobile learning-system usage: An integrated framework to measure   students'   behavioural   intention.   In Science   and Information Conference (SAI), 2014 (pp. 906-911). IEEE.

 

Aliev, A. N., & Gümrükçüoglu, A. E. (2004). Gravitational field equations on and off a 3-brane world. Classical and Quantum Gravity, 21(22), 5081.

 

Alioon, Y., & Delialioğlu, Ö. (2017). The effect of authentic m‐  learning activities on student engagement    and    motivation. British    Journal    of    Educational Technology

 

Almaiah,  M.  A.  (2018).  Acceptance  and  usage  of  a  mobile  information  system services in University of Jordan. Education and Information Technologies, 1- 23.

 

Almaiah, M. A., & Al Mulhem, A. (2018). Analysis of the essential factors affecting of  intention  to  use  of  mobile  learning  applications:  A  comparison  between universities adopters and     non-adopters. Education     and     Information Technologies, 1-36.

 

Almaiah, M. A., & Al Mulhem, A. (2019). Analysis of the essential factors affecting of  intention to  use  of  mobile  learning  applications:  A  comparison  between universities adopters and     non-adopters. Education     and     Information Technologies, 24(2), 1433-1468.

 

Almaiah, M. A., & Alismaiel, O. A. (2019). Examination of factors influencing the use of mobile learning system: An empirical study. Education and InformationTechnologies, 24(1), 885-909.

 

Almaiah, M. A., Jalil, M. A., & Man, M. (2016). Extending the TAM to examine the effects  of  quality  features  on  mobile learning acceptance. Journal of Computers in Education, 3(4), 453-485.

 

Almaiah, M. A., Jalil, M. A., & Man, M. (2016). Extending the TAM to examine the effects  of  quality  features  on  mobile learning acceptance. Journal of Computers in Education, 3(4), 453-485.

 

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended  two-step  approach. Psychological bulletin, 103(3), 411.

 

Alrasheedi, M., & Capretz, L. F. (2013, August). A meta-analysis of critical success factors  affecting  mobile  learning.  In Teaching,  Assessment  and  Learning  for Engineering  (TALE), 2013 IEEE  International Conference on (pp. 262-267). IEEE.

 

Alrasheedi, M., Capretz, L. F., & Raza, A. (2015). A systematic review of the critical factors for success of mobile learning in higher education (university students' perspective). Journal of Educational Computing Research, 52(2), 257-276.

 

Althunibat, A. (2015). Determining the factors influencing students‘ intention to use m-learning in  Jordan  higher  education. Computers  in  Human  Behavior, 52, 65-71.

 

Avellis,  G.,  Scaramuzzi,  A.,  &  Finkelstein,  A.  (2004).  Evaluating  non-functional requirements   in   mobile   learning   contents   and   multimedia   educational software. Learning with mobile devices: Research and development. London: Learning and Skills Development Agency.

 

Bere, A. (2013, October). Toward assessing the impact of mobile security issues in pedagogical   delivery:   A   mobile  learning   case   study.   In Science   and Information Conference (SAI), 2013 (pp. 363-368). IEEE.

 

Bere,  A.  (2014,  April).  Exploring determinants  for mobile  learning user  acceptance and   use:   An   application   of   UTAUT.   In Information Technology:  New Generations  (ITNG),  2014  11th  International  Conference  on (pp.  84-90). IEEE.

 

Bogdanović,  Z.,  Barać,  D.,  Jovanić,  B.,  Popović,  S.,  &  Radenković,  B.  (2014). Evaluation of  mobile  assessment  in  a  learning  management  system. BritishJournal of Educational Technology, 45(2), 231-244.

 

Briz-Ponce,   L.,   &   Juanes-Méndez,   J.   A.   (2015).   Mobile   devices   and   apps,characteristics   and   current   potential   on   learning. Journal of Information Technology Research (JITR), 8(4), 26-37.

 

Briz-Ponce,  L.,  Juanes-Méndez,  J.  A.,  García-Peñalvo,  F.  J.,  &  Pereira,  A.  (2016). Effects   of   mobile    learning    in    medical    education: a counterfactual evaluation. Journal of medical systems, 40(6), 136.

 

Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Méndez, J. A., & García-Peñalvo, F.J. (2017). Learning with mobile technologies–Students‘ behavior. Computers in Human Behavior, 72, 612-620.

 

Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Méndez, J. A., & García-Peñalvo, F.J. (2017). Learning with mobile technologies–Students‘ behavior. Computers in Human Behavior, 72, 612-620.

 

Byrne, B. M. (2001). Structural equation modeling with AMOS, EQS, and LISREL: Comparative  approaches  to  testing  for  the  factorial  validity  of  a  measuring instrument. International journal of testing, 1(1), 55-86.

 

Campbell PhD, A., & Susan, J. (2014). Performance, assessment and communication in one app: Mobile tablet assessment is here to stay. eCULTURE, 7(1), 6.

 

Chao, K. H., Chang, K. E., Lan, C. H., Kinshuk, & Sung, Y. T. (2016). Integration of mobile ARtechnology in performance assessment. Educational Technology & Society,19(4), 239–251.

 

Chaveesuk, S., Vongjaturapat, S., & Chotikakamthorn, N. (2013, October). Analysis of   factors   influencing   the   mobile   technology   acceptance   for   library information services: Conceptual model. In 2013 International Conference on Information  Technology  and  Electrical  Engineering  (ICITEE)(pp.  18-24). IEEE.

 

Chen,  C.  H.  (2010).  The  implementation  and  evaluation  of  a  mobile  self-and  peer- assessment system. Computers & Education, 55(1), 229-236.

 

Chen, C. M., & Chen, M. C. (2009). Mobile formative assessment tool based on data mining techniques    for    supporting    web-based    learning. Computers    & Education, 52(1), 256-273.

 

Chen, N. S., Wei, C. W., & Huang, Y. C. (2013). The integration of print and digital content     for     providing     learners     with     constructive     feedback     usingsmartphones. British Journal of Educational Technology, 44(5), 837-845.

 

Chen, W., Gu, X., & Wong, L. H. (2017). To click or not to click: Effectiveness ofrating  classroom  behaviors  on  academic  achievement  with  tablets. British Journal of Educational Technology.

 

Cheng, Y. M. (2015). Towards an understanding of the factors affecting m-learning acceptance:  20(3), 109-119.

 

Cheon,  J.,  Lee,  S.,  Crooks,  S.  M.,  &  Song,  J.  (2012).  An  investigation  of  mobile learning  readiness   in   higher   education   based   on   the   theory  of   planned behavior. Computers & Education, 59(3), 1054-1064.

 

Childers,  T.  L.,  Carr,  C.  L.,  Peck,  J.,  &  Carson,  S.  (2001).  Hedonic  and  utilitarian motivations  for  online  retail  shopping  behavior. Journal  of  retailing, 77(4), 511-535.

 

Chin,  W.  W.,  &  Todd,  P.  A.  (1995).  On  the  use,  usefulness,  and  ease  of  use  of structural   equation   modeling   in   MIS   research:   a   note   of   caution. MIS quarterly, 237-246.

 

Chou, P. N., Chang, C. C., & Lin, C. H. (2017). BYOD or not: A comparison of two assessment strategies for student learning. Computers in Human Behavior, 74, 63-71.

 

Chu, H. C. (2014). Potential negative effects of mobile learning on students' learning achievement and cognitive load—A format assessment perspective. Journal of Educational Technology & Society, 17(1), 332-344.

 

Chu, H. C., Hwang, G. J., Tsai, C. C., & Tseng, J. C. (2010). A two-tier test approach to  developing  location-aware  mobile  learning  systems  for  natural  science courses. Computers & Education, 55(4), 1618-1627.

 

Chung, H. H., Chen, S. C., & Kuo, M. H. (2015). A study of EFL college students‘ acceptance of mobile learning. Procedia-Social and Behavioral Sciences, 176, 333-339.

 

Coulby,  C.,  Hennessey,  S.,  Davies,  N.,  &  Fuller,  R.  (2011).  The  use  of  mobile technology   for   work‐  based   assessment:   the   student   experience. British Journal ofEducational Technology, 42(2), 251-265.

 

Crompton, H., Burke, D., & Gregory, K. H. (2017). The use of mobile learning in PK-12 education: A systematic review. Computers & Education, 110, 51-63.

 

Crompton,  H.,  Burke,  D.,  Gregory,  K.  H.,  &  Gräbe,  C.  (2016).  The  use  of  mobilelearning  in  science:  A  systematic  review. Journal  of  Science  Education  and Technology, 25(2), 149-160.

 

Dalby,  D.,  &  Swan,  M.  (2018).  Using  digital  technology  to  enhance  formative assessment   in   mathematics   classrooms. British   Journal   of   Educational Technology.

 

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology:    a comparison    of    two    theoretical    models. Management science, 35(8), 982-1003.

 

Davis,  F.  D.,  Bagozzi,  R.  P.,  &  Warshaw,  P.  R.  (1992).  Extrinsic  and  intrinsic motivation  to  use  computers  in  the  workplace  1. Journal  of  applied  social psychology, 22(14), 1111-1132.

 

Dearnley,   C.,  Haigh,   J.,  &  Fairhall,  J.  (2008).  Using  mobile  technologies   for assessment and learning in practice settings: a case study. Nurse education in practice, 8(3), 197-204.

 

Deci,  E.  L.,  &  Ryan,  R.  M.  (2002).  Overview  of  self-determination  theory:  An organismic dialectical  perspective. Handbook  of  self-determination  research, 3-33.

 

de-Marcos, L., Hilera, J. R., Barchino, R., Jiménez, L.,  Martínez, J. J., Gutiérrez, J. A., & Otón, S. (2010). An experiment for improving student‘s performance in secondary    and    tertiary  education    by    means    of    m-learning    auto- assessment. Computers & Education, 55(3), 1069-1079.

 

Fazlina,  S.,  Manap,  A.  A.,  &  Rias,  R.  M.  (2013,  September).  Mobile  learning awareness  Creative    Multimedia    (ICICM),    2013    International Conference on (pp. 226-229). IEEE.

 

Fernández-Alemán,  J.  L.,  Lopez-Gonzalez,  L.,  Gonzalez-Sequeros,  O.,  Jayne,  C., López-Jiménez, J. J., & Toval, A. (2016). The evaluation of i-SIDRA–a tool for   intelligent   feedback–in   a   course   on   the   anatomy   of   the   locomotor system. International journal of medical informatics, 94, 172-181.

 

Fuad, M., Deb, D., Etim, J., & Gloster, C. (2018). Mobile response system: a novel approach  to  interactive  and  hands-on  activity  in  the  classroom. EducationalTechnology Research and Development, 66(2), 493-514.

 

García Laborda, J. G., Magal-Royo, T. M., Litzler, M. F., & Giménez López, J. L. G.(2014).  Mobile  phones  for Spain's  university entrance  examination  language test.

 

García-Peñalvo,   F.   J.,   Ramírez-Montoya,   M.   S.,   &  García-Holgado,   A.   (2017, October). TEEM 2017 Doctoral Consortium Track. In Proceedings of the 5th International   Conference on   Technological   Ecosystems   for   Enhancing Multiculturality (p. 93). ACM.

 

Gikas,  J.,  &  Grant,  M.  M.  (2013).  Mobile  computing  devices  in  higher  education: Student perspectives  on  learning  with  cellphones,  smartphones  &  social media. The Internet and Higher Education, 19, 18-26.

 

Gu,  X.,  Gu,  F.,  &  Laffey,  J.  M.  (2011).  Designing  a  mobile  system  for  lifelong learning on the move. Journal of Computer Assisted Learning, 27(3), 204-215.

 

Ha,  I.,  Yoon,  Y.,  &  Choi,  M.  (2007).  Determinants  of  adoption  of  mobile  games under mobile    broadband    wireless    access    environment. Information & management, 44(3), 276-286.

 

Hao,  S.,  Dennen,  V.  P.,  &  Mei,  L.  (2017).  Influential  factors  for  mobile  learning acceptance   among   Chinese   users. Educational   Technology   Research   and Development, 65(1), 101-123.

 

Harchay, A., Cheniti-Belcadhi, L., & Braham, R. (2015). A Context-aware Approach for Personalized Mobile Self-Assessment. J. UCS, 21(8), 1061-1085.

 

Harchay,  A.,  Cheniti-Belcadhi,  L.,  &  Braham,  R.  (2017,  October).  MobiSWAP: Personalized  Mobile  Assessment  Tool  Based  on  Semantic  Web  and  Web Services.  In 2017  IEEE/ACS  14th  International  Conference  on  Computer Systems and Applications (AICCSA) (pp. 1406-1413). IEEE.

 

Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of marketing, 60(3), 50-68.

 

Hoyle, R. H. (1995). Structural  equation modeling:Concepts, issues, and applications. Sage.

 

Huang, C. Y. (2012, November). A comparison of fuzzy DNP and SEM in analyzing novel  mobile  learning  technology  acceptances  by  learners.  In Fuzzy  Theory and  it's  Applications  (iFUZZY),  2012  International  Conference  on (pp.  119-124). IEEE.

 

Huang,  Y.  M.,  Lin,  Y.  T.,  &  Cheng,  S.  C.  (2009).  An  adaptive  testing  system  forsupporting  versatile  educational  assessment. Computers  &  Education, 52(1), 53-67. Human Behavior, 27(2), 890e898.

 

Hung,  P.  H.,  Hwang,  G.  J.,  Lin,  Y.  F.,  Wu,  T.  H.,  &  Su,  I.  H.  (2013).  Seamless connection  between  learning  and  assessment-applying  progressive  learning tasks   in   mobile  ecology   inquiry. Journal   of   Educational   Technology   & Society, 16(1), 194-205.

 

Hung,  P.  H.,  Lin,  Y.  F.,  &  Hwang,  G.  J.  (2010).  Formative  assessment  design  for PDA   integrated      ecology     observation. Educational      Technology      & Society, 13(3), 33-42.

 

Hwang, G. J., & Chang, H. F. (2011). A formative assessment-based mobile learning approach    to    improving    the    learning    attitudes    and    achievements    of students. Computers & Education, 56(4), 1023-1031.

 

Igbaria,  M.,  Iivari,  J.,  &  Maragahh,  H.  (1995).  Why  do  individuals  use  computer technology?  A  Finnish  case  study. Information  &  management, 29(5),  227- 238.

 

Illingworth, A. J., Morelli, N. A., Scott, J. C., & Boyd, S. L. (2015). Internet-based, unproctored assessments   on   mobile   and   non-mobile   devices:   Usage, measurement    equivalence,    and    outcomes. Journal    of    Business     and Psychology, 30(2), 325-343.

 

Johnson,  L.,  Becker,  S.  A.,  Cummins,  M.,  Estrada,  V.,  Freeman,  A.,  &  Hall,  C. (2016). NMC  horizon  report:  2016  higher  education  edition (pp.  1-50).  The New Media Consortium.

 

Karadeniz,  Ş.  (2009).  The  impacts  of  paper,  web  and  mobile  based  assessment  on student‘s achievement and perceptions. Scientific Research and Essays, 4(10), 984-991.

 

Karadeniz,  S.  (2011).  Effects  of  gender  and  test  anxiety on  student  achievement  in mobile based assessment. Procedia-Social and Behavioral Sciences, 15, 3173- 3178.

 

Khalifa, M., & Ning Shen, K. (2008). Explaining the adoption of transactional B2C mobile commerce. Journal of enterprise information management, 21(2), 110- 124.

 

Kim, B., Choi, M., & Han, I. (2009). User behaviors toward mobile data services: The role    of    perceived    fee    and    prior    experience. Expert    Systems    withApplications, 36(4), 8528-8536.

 

Kitchenham,   B.,   &   Charters,   S.   (2007).   Guidelines   for   performing   systematicliterature reviews in software engineering.

 

Kuh, G. D., Jankowski, N., Ikenberry, S. O., & Kinzie, J. L. (2014). Knowing what students  know  and  can  do:  The  current  state  of  student  learning  outcomes assessment in US colleges and universities. Champaign, IL: National Institute for Learning Outcomes Assessment.

 

Laborda, J. G., Royo, T. M., Litzler, M. F., & López, J. L. G. (2014). Mobile phones for   Spain's  university   entrance   examination   language   test. Journal   of Educational Technology & Society, 17(2), 17-30.

 

Lai,   C.   L.,   &   Hwang,   G.   J.   (2015).   An   interactive   peer-assessment   criteria development  approach  to  improving  students'  art  design  performance  using handheld devices. Computers & Education, 85, 149-159.

 

Lai, C. L., Hwang, G. J., & Tu, Y. H. (2018). The effects of computer-supported self- regulation  in  science  inquiry  on  learning  outcomes,  learning  processes,  and self-efficacy. Educational Technology Research and Development, 1-30.

 

Lam,  L.  (2015,  July).  A  Qualitative  Study  to  Understand  the  Factors  Influencing Student  Acceptance  of  Mobile  Learning.  In Educational  Technology  (ISET), 2015 International Symposium on (pp. 158-162). IEEE.

 

Lee, M. K., Cheung, C. M., & Chen, Z. (2005). Acceptance of Internet-based learning medium:   the   role   of   extrinsic   and   intrinsic   motivation. Information   & management, 42(8), 1095-1104.

 

Lee,     Y.     E.,     &     Benbasat,     I.     (2003).     Interface     design     for     mobile commerce. Communications of the ACM, 46(12), 48-52.

 

Liu,  Y.,  &  Li,  H.  (2011).  Exploring  the  impact  of  use  context  on  mobile  hedonic services adoption: An empirical study on mobile gaming in China. Computers in Human Behavior, 27(2), 890-898.

 

Looi,  C.  K.,  Zhang,  B.,  Chen,  W.,  Seow,  P.,  Chia,  G.,  Norris,  C.,  &  Soloway,  E. (2011). 1: 1 mobile inquiry learning experience for primary science students: A    study    of    learning    effectiveness. Journal    of    Computer    Assisted Learning, 27(3), 269-287.

 

Lu,  A.,  Chen,  Q.,  Zhang,  Y.,  &  Chang,  T.  (2016,  December).  Investigating  the Determinants of Mobile Learning Acceptance in Higher Education Based on UTAUT.  In 2016  International  Computer  Symposium  (ICS) (pp.  651-655).IEEE.

 

Lu,  Q.,  Yu,  Y.,  Ma,  Q.,  Chen,  B.,  &  Zhang,  H.  (2016).  2D  transition‐  metal‐ dichalcogenide‐  nanosheet‐  based     composites     for     photocatalytic     and electrocatalytic   hydrogen   evolution   reactions. Advanced   Materials, 28(10), 1917-1933.

 

Mac Callum, K., & Jeffrey, L. (2014). Comparing the role of ICT literacy and anxiety in the adoption of mobile learning. Computers in Human Behavior, 39, 8-19.

 

Marangunić,  N.,  &  Granić,  A.  (2015).  Technology  acceptance  model:  a  literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81-95.

 

Merhi, M. I. (2015). Factors influencing higher education students to adopt podcast: An empirical study. Computers & Education, 83, 32-43.

 

Milošević, I., Živković, D., Manasijević, D., & Nikolić, D. (2015). The effects of the intended behavior of students in the use of M-learning. Computers in Human Behavior, 51, 207-215.

 

Miyasawa, Y., & Ueno, M. (2013, July). Mobile testing for authentic assessment in the    field.    In International    Conference    on    Artificial    Intelligence    in Education (pp. 619-623). Springer, Berlin, Heidelberg.

 

Nedungadi, P., & Raman, R. (2012). A new approach to personalization: integrating e-learning  and     m-learning. Educational     Technology     Research     and Development, 60(4), 659-678.

 

Nikou, S. A., & Economides, A. A. (2014, November). A model for MBA adoption based  on  Self-Determination  Theory  of  Motivation.  In Interactive  Mobile Communication   Technologies   and   Learning   (IMCL),   2014   International Conference on (pp. 86-90). IEEE.

 

Nikou,  S.  A.,  &  Economides,  A.  A.  (2015,  November).  The  effects  of  perceived mobility  and  satisfaction  on  the  adoption  of  MBA.  In Interactive  Mobile Communication   Technologies and   Learning   (IMCL),   2015   International Conference on (pp. 167-171). IEEE.

 

Nikou,  S.  A.,  &  Economides,  A.  A.  (2016).  An  outdoor  MBA  activity:  Measuring students'  motivation   and   acceptance. International   Journal   of   Interactive Mobile Technologies, 10(4), 11-17.

 

Nikou,  S.  A.,  &  Economides,  A.  A.  (2016).  The  impact  of  paper-based,  computer- based  and  mobile-based  self-assessment  on  students'  science  motivation  andt. Computers in Human Behavior, 55, 1241-1248.

 

Nikou,  S.  A.,  &  Economides,  A.  A.  (2017).  MBA:  Integrating  acceptance  and motivational factors into a combined model of Self-Determination Theory and Technology Acceptance. Computers in Human Behavior, 68, 83-95.

 

Nikou,  S.  A.,  &  Economides,  A.  A.  (2017).  MBA:  Investigating  the  factors  that influence 

behavioral intention to use. Computers & Education, 109, 56-73.

 

Nikou,  S.  A.,  &  Economides,  A.  A.  (2017,  April).  MBA:  Towards  a  motivational framework. In 2017    IEEE    Global    Engineering    Education    Conference (EDUCON) (pp. 1522-1526). IEEE.

 

Nikou, S. A., & Economides, A. A. (2019). Factors that influence behavioral intention to  use  mobile‐  based  assessment:  A  STEM  teachers‘  perspective. British Journal of Educational Technology, 50(2), 587-600.

 

Nikou, S. A., & Economides, A. A. (2018). MBA: A literature review of publications in  major  referred  journals  from  2009  to  2018. Computers  & Education, 125, 101-119.

 

Nikou,  S.  A.,  &  Economides,  A.  A.  (2018).  Mobile‐  Based  micro‐  Learning  and Assessment: Impact  on  learning  performance  and  motivation  of  high  school students. Journal of Computer Assisted Learning, 34(3), 269-278.

 

Nikou, S., & Economides, A. A. (2013). Student achievement in paper, computer/web and mobile based assessment.

 

Nitsche, K. (2013, July). Acceptance of mobile, classroom-bound e-Learning systems from   the   perspective   of   students   and   lectures.   In Advanced   Learning Technologies (ICALT), 2013 IEEE 13th International Conference on (pp. 508- 509). IEEE.

 

Norazah,  M.  N.,  Ridzwan,  C.  R.,  &  Arif,  A.  A.  (2013).  Relationship  between  the acceptance  of  mobile  learning  for  AutoCAD  course  and  learning  style  in polytechnic. Procedia-Social and Behavioral Sciences, 102, 177-187.

 

Ozdamli,   F.   (2012).   Pedagogical   framework   of   m-learning. Procedia-Social   andBehavioral Sciences, 31, 927-931.

 

Park, E., Baek, S., Ohm, J., & Chang, H. J. (2014). Determinants of player acceptance of  mobile  social  network  games:  An  application  of  extended  technologyacceptance model. Telematics and Informatics, 31(1), 3-15.

 

Park,  S.  Y.,  Nam,  M.  W.,  &  Cha,  S.  B.  (2012).  University  students'  behavioralintention   to   use   mobile   learning:   Evaluating   the   technology   acceptance model. British Journal of Educational Technology, 43(4), 592-605.

 

Paturusi, S., Chisaki, Y., Usagawa, T., & Lumenta, A. (2015, September). A study of students' acceptance toward mobile learning in higher education institution in Indonesia.     In 2015     International     Conference     on     Information     & Communication Technology and Systems (ICTS) (pp. 193-196). IEEE.

 

Pimmer, C., Mateescu, M., & Gröhbiel, U. (2016). Mobile and ubiquitous learning in higher      education     settings.     A     systematic     review     of      empirical studies. Computers in Human Behavior, 63, 490-501.

 

Poong,  Y.  S.,  Yamaguchi,  S.,  &  Takada,  J.  I.  (2017).  Investigating  the  drivers  of mobile learning acceptance among young adults in the World Heritage town of Luang Prabang, Laos. Information Development, 33(1), 57-71.

 

Pu,  Y.  H.,  Wu,  T.  T.,  Chiu,  P.  S.,  &  Huang,  Y.  M.  (2016).  The  design  and implementation  of  authentic  learning  with  mobile  technology  in  vocational nursing  practice course. British  Journal  of  Educational  Technology, 47(3), 494-509.

 

Roschelle,  J.,  Rafanan,  K.,  Bhanot,  R.,  Estrella,  G.,  Penuel,  B.,  Nussbaum,  M.,  & Claro, S. (2010). Scaffolding group explanation and feedback with handheld technology:     impact   on     students‘     mathematics     learning. Educational Technology Research and Development, 58(4), 399-419.

 

Rossing,  J.  P.,  Miller,  W.,  Cecil,  A.  K.,  &  Stamper,  S.  E.  (2012).  iLearning:  The future  of  higher  education?  Student  perceptions  on  learning  with  mobile tablets.

 

Sabah,  N.  M.  (2016).  Exploring  students'  awareness  and  perceptions:  Influencing factors and individual differences driving m-learning adoption. Computers in Human Behavior, 65, 522-533.

 

Salkind,  N.  J.,  &  Rasmussen,  K.  (2007).  Kruskal-Wallis  One-Way  Analysis  of Variance. Encyclopedia of Measurement and Statistics, 2, 519-521.

 

Samaie,  M.,  Mansouri  Nejad,  A.,  &  Qaracholloo,  M.  (2018).  An  inquiry  into  the efficiency  of  WhatsApp  for  self‐  and  peer‐  assessments  of  oral  language proficiency. British Journal of Educational Technology, 49(1), 111-126.

 

Sánchez-Prieto,   J.   C.,   Olmos-Migueláñez,   S.,   &   García-Peñalvo,   F.   J.   (2016).Informal  tools  in  formal  contexts:  Development  of  a  model  to  assess  theacceptance  of  mobile  technologies  among  teachers. Computers  in  HumanBehavior, 55, 519-528.

 

Sánchez-Prieto,   J.   C.,   Olmos-Migueláñez,   S.,   &   García-Peñalvo,   F.   J.   (2017). MLearning   and   pre-service   teachers:   An   assessment   of   the   behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644-654.

 

Santos, P., Hernández-Leo, D., Pérez-Sanagustín, M., & Blat, J. (2012). Modeling the computing-based testing domain extending IMS QTI: Framework, models and exemplary  implementations. Computers   in   Human   Behavior, 28(5),   1648- 1662.

 

Santos,   P.,   PéRez-SanagustíN,   M.,   HernáNdez-Leo,   D.,   &   Blat,   J.   (2011). QuesTInSitu: From tests to routes for assessment in situ activities. Computers & Education, 57(4), 2517-2534.

 

Sarrab,   M.   (2015).   M-learning   in   education:   Omani   Undergraduate   students‘ perspective. Procedia-Social and Behavioral Sciences, 176, 834-839.

 

Sarrab, M., Al-Shihi, H., & Khan, A. I. (2015, December). An empirical analysis of mobile  learning (m-learning)  awareness  and  acceptance  in  higher  education. In Computing  and  Network  Communications  (CoCoNet),  2015  International Conference on (pp. 960-963). IEEE.

 

Sharma,  S.  K.,  Sarrab,  M.,  &  Al-Shihi,  H.  (2017).  Development  and  validation  of Mobile  Learning         Acceptance         Measure. Interactive         Learning Environments, 25(7), 847-858.

 

Shee,  D.  Y.,  &  Wang,  Y.  S.  (2008).  Multi-criteria  evaluation  of  the  web-based  e- learning   system:   A   methodology   based   on   learner   satisfaction   and   its applications. Computers & Education, 50(3), 894-905.

 

So, S. (2016). Mobile instant messaging support for teaching and learning in higher education. The Internet and Higher Education, 31, 32-42.

 

Song,  Y.,  &  Kong,  S.  C.  (2017).  RETRACTED:  Affordances  and  constraints  of BYOD   (Bring  Your   Own   Device)   for   learning   and   teaching   in   higher education: Teachers' perspectives.

 

Stowell,   J.   R.   (2015).   Use   of   clickers   vs.   mobile   devices   for   classroompolling. Computers & Education, 82, 329-334.

 

Sun,  J.  C.  Y.  (2014).  Influence  of  polling  technologies  on  student  engagement:  An analysis   of   student   motivation,   academic   performance,   and   brainwave data. Computers & Education, 72, 80-89.

 

Sung,  Y.  T.,  Chang,  K.  E.,  &  Liu,  T.  C.  (2016).  The  effects  of  integrating  mobile devices with teaching and learning on students' learning performance: A meta- analysis and research synthesis. Computers & Education, 94, 252-275.

 

Tamboli,  M.  A.,  &  Biswas,  P.  K.  (2015,  October).  Mobile  Learning  Applications' Acceptance     Model     (MLAAM).     In Computing     and     Communication (IEMCON), 2015 International Conference and Workshop on (pp. 1-6). IEEE.

 

Tan, G. W. H., Ooi, K. B., Leong, L. Y., & Lin, B. (2014). Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach. Computers in Human Behavior, 36, 198-213.

 

Tarighat,   S.,   &  Khodabakhsh,   S.   (2016).   Mobile-assisted   language   assessment: Assessing speaking. Computers in Human Behavior, 64, 409-413.

 

Teo,  T.  S.,  Lim,  V.  K.,  &  Lai,  R.  Y.  (1999).  Intrinsic  and  extrinsic  motivation  in Internet usage. Omega, 27(1), 25-37.

 

Terzis, V., & Economides, A. A. (2011). The acceptance and use of computer-based assessment. Computers & Education, 56(4), 1032-1044.

 

Tucker,    S.    P.    (2008).    E-commerce    standard    user    interface:    an    E-menu system. Industrial Management & Data Systems, 108(8), 1009-1028.

 

Valencia,  S.  W.,  Martin,  S.  D.,  Place,  N.  A.,  &  Grossman,  P.  (2009).  Complex interactions  in  student  teaching:  Lost  opportunities  for  learning. Journal  of Teacher Education, 60(3), 304-322.

 

Van  der  Heijden,  H.  (2004).  User  acceptance  of  hedonic  information  systems. MIS quarterly, 695-704.

 

van  der  Schaaf,  M.,  Donkers,  J.,  Slof,  B.,  Moonen-van  Loon,  J.,  van  Tartwijk,  J., Driessen, E., & Ten Cate, O. (2017). Improving workplace-based assessment and feedback by an E-portfolio enhanced with learning analytics. Educational Technology Research and Development, 65(2), 359-380.

 

Venkatesh,  V.,  &  Bala,  H.  (2008).  Technology  acceptance  model  3  and  a  research agenda on interventions. Decision sciences, 39(2), 273-315.

 

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.

 

Wang,   A.   I.   (2015).   The   wear   out   effect   of   a   game-based   student   response

system. Computers & Education, 82, 217-227.

 

Zbick, J., Nake, I., Milrad, M., & Jansen, M. (2015, July). A web-based framework to design   and   deploy   mobile   learning   activities:   Evaluating   its   usability, learnability  and  acceptance.  In Advanced  Learning  Technologies  (ICALT), 2015 IEEE 15th International Conference on (pp. 88-92). IEEE.

 

Zhai, X., Zhang, M., & Li, M. (2018). One‐  to‐  one mobile technology in high school physics  classrooms:  Understanding  its  use  and  outcome. British  Journal  of Educational Technology, 49(3), 516-532.

 

Zhang, J., Chang, C., & Zhou, P. (2015, October). Factors affecting the acceptance of mobile   devices   in   the   classroom.    In Educational   Innovation   through Technology (EITT), 2015 International Conference of (pp. 294-298). IEEE.

 

Zydney,  J.  M.,  &  Warner,  Z.  (2016).  Mobile  apps  for  science  learning:  Review  of research. Computers & Education, 94, 1-17.